From eedbbb918c763efee518e0db8453cd254f577ec0 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 1 Mar 2026 21:16:44 +0100 Subject: [PATCH 1/7] Security updates --- .gitignore | 1 + notebooks/demo_linearboost_usage.ipynb | 1395 ++++++++++++++++++++++-- requirements.txt | 1 + src/linearboost/__init__.py | 7 +- src/linearboost/linear_boost.py | 4 + 5 files changed, 1295 insertions(+), 113 deletions(-) diff --git a/.gitignore b/.gitignore index 008e237..04e41e6 100644 --- a/.gitignore +++ b/.gitignore @@ -109,6 +109,7 @@ venv/ ENV/ env.bak/ venv.bak/ +benchmark/ # Spyder project settings .spyderproject diff --git a/notebooks/demo_linearboost_usage.ipynb b/notebooks/demo_linearboost_usage.ipynb index 7b3b656..4d4fefc 100644 --- a/notebooks/demo_linearboost_usage.ipynb +++ b/notebooks/demo_linearboost_usage.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 42, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -52,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -60,7 +60,7 @@ "from sklearn.preprocessing import LabelEncoder\n", "\n", "# The Huberman's Survival's id on UCI Machine Learning Repository\n", - "dataset_id = 43\n", + "dataset_id = 52\n", "\n", "dataset = fetch_ucirepo(id=dataset_id)\n", "\n", @@ -70,17 +70,38 @@ "\n", "label_encoder = LabelEncoder()\n", "\n", - "y = label_encoder.fit_transform(y.values.ravel())" + "y = label_encoder.fit_transform(y.values.ravel())\n", + "import numpy as np\n", + "\n", + "y = np.where(np.isin(y, [2, 3, 4, 5]), 1, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, ..., 0, 0, 0], shape=(4601,))" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ - "import pandas as pd\n", - "\n", "# Identify categorical columns\n", "categorical_cols = X.select_dtypes(include=[\"object\"]).columns.tolist()\n", "\n", @@ -101,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -122,57 +143,375 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "[I 2025-07-28 20:32:30,509] A new study created in memory with name: no-name-39689138-b2a1-447a-af63-be7733a7aeb8\n", - "[I 2025-07-28 20:32:30,764] Trial 0 finished with value: 0.7283291353857195 and parameters: {'n_estimators': 256, 'learning_rate': 0.11807746849928968, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.10360685199357951}. Best is trial 0 with value: 0.7283291353857195.\n", - "[I 2025-07-28 20:32:32,767] Trial 1 finished with value: 0.7323671972329208 and parameters: {'n_estimators': 363, 'learning_rate': 0.013883181171194234, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.3980809182349502}. Best is trial 1 with value: 0.7323671972329208.\n", - "...", - "[I 2025-07-28 20:34:42,444] Trial 199 finished with value: 0.7515000210035615 and parameters: {'n_estimators': 245, 'learning_rate': 0.06109405565734974, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.08461411124525335}. Best is trial 167 with value: 0.7583125868901313.\n" + "[I 2025-08-19 22:02:02,037] A new study created in memory with name: no-name-82933463-2c1e-432a-893e-8dccaf42a971\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:02:02,719] Trial 0 finished with value: 0.6404040390084329 and parameters: {'n_estimators': 98, 'learning_rate': 0.025040969870000332, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.0036506834438673618, 'degree': 5, 'coef0': 0.3301750124911056}. Best is trial 0 with value: 0.6404040390084329.\n", + "[I 2025-08-19 22:02:03,124] Trial 1 finished with value: 0.5345075877473346 and parameters: {'n_estimators': 223, 'learning_rate': 0.7297126647372456, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.8114762985242304, 'degree': 3, 'coef0': 0.427337620015356}. Best is trial 0 with value: 0.6404040390084329.\n", + "[I 2025-08-19 22:02:03,558] Trial 2 finished with value: 0.8435145697001879 and parameters: {'n_estimators': 400, 'learning_rate': 0.11869138844012254, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.005788104394731735}. Best is trial 2 with value: 0.8435145697001879.\n", + "[I 2025-08-19 22:02:03,711] Trial 3 finished with value: 0.8764210138920593 and parameters: {'n_estimators': 31, 'learning_rate': 0.030091383187136795, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 3 with value: 0.8764210138920593.\n", + "[I 2025-08-19 22:02:04,570] Trial 4 finished with value: 0.8185946867313308 and parameters: {'n_estimators': 319, 'learning_rate': 0.024091883364845683, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'linear'}. Best is trial 3 with value: 0.8764210138920593.\n", + "[I 2025-08-19 22:02:04,750] Trial 5 finished with value: 0.9017212906585973 and parameters: {'n_estimators': 87, 'learning_rate': 0.48142547555682524, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.12840098702472594}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:05,166] Trial 6 finished with value: 0.8300528334061669 and parameters: {'n_estimators': 86, 'learning_rate': 0.2164714650817863, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'sigmoid', 'gamma': 0.15920891724378544, 'coef0': 0.7539946866285475}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:07,510] Trial 7 finished with value: 0.6535195434381997 and parameters: {'n_estimators': 470, 'learning_rate': 0.012901892094153418, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'poly', 'gamma': 3.940362684702575, 'degree': 2, 'coef0': 0.4967650580245552}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:07,913] Trial 8 finished with value: 0.7971266517319944 and parameters: {'n_estimators': 452, 'learning_rate': 0.43676541330692303, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.0967500612488954}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,322] Trial 9 finished with value: 0.5694014450011219 and parameters: {'n_estimators': 243, 'learning_rate': 0.012286177632393586, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.0026004536254413, 'degree': 4, 'coef0': 0.15054572715819692}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,587] Trial 10 finished with value: 0.8819567586691062 and parameters: {'n_estimators': 157, 'learning_rate': 0.2770406446126875, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.05370625210928932}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,829] Trial 11 finished with value: 0.8964421634266355 and parameters: {'n_estimators': 147, 'learning_rate': 0.3006331948489542, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.03955509407249669}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,971] Trial 12 finished with value: 0.8521240202153993 and parameters: {'n_estimators': 172, 'learning_rate': 0.9988817093993582, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.023490983805136197}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:10,237] Trial 13 finished with value: 0.9263770712127013 and parameters: {'n_estimators': 35, 'learning_rate': 0.10250765731473209, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.6514127677245307}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:10,424] Trial 14 finished with value: 0.7085679744920659 and parameters: {'n_estimators': 21, 'learning_rate': 0.07966081404443828, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'sigmoid', 'gamma': 0.6310102946471119, 'coef0': 0.9639953544051878}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:10,506] Trial 15 finished with value: 0.5418932173176405 and parameters: {'n_estimators': 315, 'learning_rate': 0.08759215611783155, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 8.453910649175267}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:10,948] Trial 16 finished with value: 0.9031163163136877 and parameters: {'n_estimators': 76, 'learning_rate': 0.052469928102373574, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.5675836541180403}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:11,057] Trial 17 finished with value: 0.7550115293636145 and parameters: {'n_estimators': 13, 'learning_rate': 0.044871824661281395, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8086407703773626}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:11,526] Trial 18 finished with value: 0.53092297245577 and parameters: {'n_estimators': 78, 'learning_rate': 0.1330897164081811, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 2.267555816096478, 'coef0': 0.014870765902805116}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:12,002] Trial 19 finished with value: 0.8675858847685067 and parameters: {'n_estimators': 207, 'learning_rate': 0.05154796109273011, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:12,485] Trial 20 finished with value: 0.9088656344540121 and parameters: {'n_estimators': 303, 'learning_rate': 0.16750558381714575, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.29744031601691207}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:12,954] Trial 21 finished with value: 0.9206498285402447 and parameters: {'n_estimators': 299, 'learning_rate': 0.17348345914734523, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.5243817676865739}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:13,447] Trial 22 finished with value: 0.9115464653740457 and parameters: {'n_estimators': 309, 'learning_rate': 0.1966185423007268, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.27828466414571096}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:14,378] Trial 23 finished with value: 0.9462108116357341 and parameters: {'n_estimators': 369, 'learning_rate': 0.16073435877818204, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9847789259555744}. Best is trial 23 with value: 0.9462108116357341.\n", + "[I 2025-08-19 22:02:15,192] Trial 24 finished with value: 0.9461696031015109 and parameters: {'n_estimators': 361, 'learning_rate': 0.07835520681588722, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.0987046014422583}. Best is trial 23 with value: 0.9462108116357341.\n", + "[I 2025-08-19 22:02:16,105] Trial 25 finished with value: 0.9517798886901965 and parameters: {'n_estimators': 375, 'learning_rate': 0.07269841814479387, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.209952371165283}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:16,984] Trial 26 finished with value: 0.9324487995962987 and parameters: {'n_estimators': 379, 'learning_rate': 0.07230657816758931, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4187279689074788}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:18,776] Trial 27 finished with value: -inf and parameters: {'n_estimators': 374, 'learning_rate': 0.038575969507376164, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 4.714383316597883, 'coef0': 0.7803535797752535}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:19,167] Trial 28 finished with value: 0.8709779688748764 and parameters: {'n_estimators': 421, 'learning_rate': 0.0746916847815778, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:21,551] Trial 29 finished with value: 0.7023921951486901 and parameters: {'n_estimators': 498, 'learning_rate': 0.02085363052154944, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 1.759102678934659, 'degree': 2, 'coef0': 0.6913894433614183}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:21,919] Trial 30 finished with value: 0.859909045397919 and parameters: {'n_estimators': 350, 'learning_rate': 0.060559050608611484, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.4952186713052695}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:23,126] Trial 31 finished with value: 0.9218746518721318 and parameters: {'n_estimators': 354, 'learning_rate': 0.1280653186238248, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8616818169187364}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:23,988] Trial 32 finished with value: 0.9296865784287618 and parameters: {'n_estimators': 410, 'learning_rate': 0.07021730970300748, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7746356369809244}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:24,184] Trial 33 finished with value: 0.8116240901405313 and parameters: {'n_estimators': 276, 'learning_rate': 0.10871708293585933, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 9.388110391883588}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:25,695] Trial 34 finished with value: 0.9293560948390669 and parameters: {'n_estimators': 383, 'learning_rate': 0.034156266307402705, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.429084842782736}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:25,856] Trial 35 finished with value: 0.5852644581410708 and parameters: {'n_estimators': 426, 'learning_rate': 0.1511859326143314, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 1.2486026815845557, 'degree': 5, 'coef0': 0.9704353144695104}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:26,306] Trial 36 finished with value: 0.8763231749616842 and parameters: {'n_estimators': 344, 'learning_rate': 0.09526097425921956, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:27,781] Trial 37 finished with value: 0.9018423220481535 and parameters: {'n_estimators': 380, 'learning_rate': 0.019876822774381235, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.724771837650152}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:28,517] Trial 38 finished with value: 0.9202747486761362 and parameters: {'n_estimators': 453, 'learning_rate': 0.06647223380069087, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.1084783848378548}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:28,942] Trial 39 finished with value: 0.8628370095777891 and parameters: {'n_estimators': 273, 'learning_rate': 0.269922262432126, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.0066123931064254555}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:30,565] Trial 40 finished with value: 0.8050021872275455 and parameters: {'n_estimators': 332, 'learning_rate': 0.02933776477103744, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 0.27010729641241976, 'coef0': 0.22133988641045943}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:31,335] Trial 41 finished with value: 0.9268901508585747 and parameters: {'n_estimators': 411, 'learning_rate': 0.061902309242806756, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.8646613129693383}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:32,431] Trial 42 finished with value: 0.9240947416940678 and parameters: {'n_estimators': 398, 'learning_rate': 0.042508608956588166, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.786058859203096}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:32,890] Trial 43 finished with value: 0.8712087231269168 and parameters: {'n_estimators': 441, 'learning_rate': 0.07930266596666663, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.848021414105109}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:33,835] Trial 44 finished with value: 0.8991133617676276 and parameters: {'n_estimators': 365, 'learning_rate': 0.12330246274809091, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.450448896004862}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:34,438] Trial 45 finished with value: 0.6983797615900317 and parameters: {'n_estimators': 482, 'learning_rate': 0.05239332207965422, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 5.714276346847359, 'degree': 3, 'coef0': 0.6186051595258996}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:34,863] Trial 46 finished with value: 0.9293575787426139 and parameters: {'n_estimators': 394, 'learning_rate': 0.22829327401274127, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.9319488463371248}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:35,220] Trial 47 finished with value: 0.8181102705094435 and parameters: {'n_estimators': 439, 'learning_rate': 0.35502195035823503, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:36,664] Trial 48 finished with value: 0.846325632333387 and parameters: {'n_estimators': 469, 'learning_rate': 0.09448870280660304, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.0010087705216177958}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,219] Trial 49 finished with value: 0.9378935239732582 and parameters: {'n_estimators': 334, 'learning_rate': 0.07222234799412496, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.4323404856498683}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,371] Trial 50 finished with value: 0.932192378562819 and parameters: {'n_estimators': 334, 'learning_rate': 0.675761337925708, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3921347754260098}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,533] Trial 51 finished with value: 0.920993572883402 and parameters: {'n_estimators': 331, 'learning_rate': 0.8027321262951309, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.395150239747632}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,949] Trial 52 finished with value: 0.9459583919276465 and parameters: {'n_estimators': 283, 'learning_rate': 0.5044135952817085, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.9424173881795572}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:38,333] Trial 53 finished with value: 0.9543374173629988 and parameters: {'n_estimators': 239, 'learning_rate': 0.5595716808885748, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.647241725838371}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:38,436] Trial 54 finished with value: 0.8514265280726686 and parameters: {'n_estimators': 227, 'learning_rate': 0.48409844695819165, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 4.125551830420961}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:38,683] Trial 55 finished with value: 0.8281731307797214 and parameters: {'n_estimators': 193, 'learning_rate': 0.5985975447789242, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.586444926695531}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:38,721] Trial 56 finished with value: -inf and parameters: {'n_estimators': 278, 'learning_rate': 0.3864373743263281, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 9.558029039004188, 'coef0': 0.02372150656881622}. Best is trial 53 with value: 0.9543374173629988.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "Trial failed with exception: \n", + "All the 10 fits failed.\n", + "It is very likely that your model is misconfigured.\n", + "You can try to debug the error by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/pipeline.py\", line 662, in fit\n", + " self._final_estimator.fit(Xt, y, **last_step_params[\"fit\"])\n", + " ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 628, in fit\n", + " return super().fit(training_data, y, sample_weight)\n", + " ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/ensemble/_weight_boosting.py\", line 167, in fit\n", + " sample_weight, estimator_weight, estimator_error = self._boost(\n", + " ~~~~~~~~~~~^\n", + " iboost, X, y, sample_weight, random_state\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 702, in _boost\n", + " raise ValueError(\n", + " \"BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\"\n", + " )\n", + "ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:02:39,055] Trial 57 finished with value: 0.8717863235369474 and parameters: {'n_estimators': 257, 'learning_rate': 0.5013464948241906, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.4424401922925503}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:39,588] Trial 58 finished with value: 0.6882396202694265 and parameters: {'n_estimators': 293, 'learning_rate': 0.31142751907125016, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'poly', 'gamma': 3.613839721994584, 'degree': 4, 'coef0': 0.32280671741188566}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:39,778] Trial 59 finished with value: 0.8819539998922167 and parameters: {'n_estimators': 233, 'learning_rate': 0.6097668080397359, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.08883583450139441}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:40,441] Trial 60 finished with value: 0.9281749115310631 and parameters: {'n_estimators': 204, 'learning_rate': 0.1538995463327668, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.9153016198187663}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:40,637] Trial 61 finished with value: 0.9239378580080395 and parameters: {'n_estimators': 361, 'learning_rate': 0.8920930290523721, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.069795607208937}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:41,236] Trial 62 finished with value: 0.9377972940442809 and parameters: {'n_estimators': 319, 'learning_rate': 0.08221986476116154, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2190944381431885}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:41,517] Trial 63 finished with value: 0.862790627424238 and parameters: {'n_estimators': 317, 'learning_rate': 0.08593415530250405, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.749002498833249}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:42,108] Trial 64 finished with value: 0.9353188132686524 and parameters: {'n_estimators': 257, 'learning_rate': 0.0561150028803941, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7932014212856044}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:42,349] Trial 65 finished with value: 0.8649001790723136 and parameters: {'n_estimators': 297, 'learning_rate': 0.11050826854916225, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:43,076] Trial 66 finished with value: 0.9266398313868034 and parameters: {'n_estimators': 118, 'learning_rate': 0.04607008180795451, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8383575083908024}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:44,106] Trial 67 finished with value: 0.9546503958241553 and parameters: {'n_estimators': 247, 'learning_rate': 0.21347325986729773, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1809425528201563}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:44,846] Trial 68 finished with value: 0.6989186486192198 and parameters: {'n_estimators': 236, 'learning_rate': 0.429627157442039, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 0.012260381856754793, 'coef0': 0.8372686886361344}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:45,094] Trial 69 finished with value: 0.9354147103952727 and parameters: {'n_estimators': 173, 'learning_rate': 0.18642494354170872, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.476492775061456}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:45,787] Trial 70 finished with value: 0.9293575787426139 and parameters: {'n_estimators': 282, 'learning_rate': 0.14066067971814394, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.6966820470759123}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:46,568] Trial 71 finished with value: 0.9544562382246768 and parameters: {'n_estimators': 265, 'learning_rate': 0.22209149104576692, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2304812552325375}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:47,354] Trial 72 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 254, 'learning_rate': 0.2565268037020722, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8661220775520375}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:48,126] Trial 73 finished with value: 0.9546241015332697 and parameters: {'n_estimators': 210, 'learning_rate': 0.2281741451600984, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.936522572088527}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:48,879] Trial 74 finished with value: 0.9517579938498862 and parameters: {'n_estimators': 210, 'learning_rate': 0.2191416530172179, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6401238802616942}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:49,874] Trial 75 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 214, 'learning_rate': 0.22967638326768033, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.635572239547895}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:50,292] Trial 76 finished with value: 0.9283794764556614 and parameters: {'n_estimators': 214, 'learning_rate': 0.23287522337623806, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.3983494805126542}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:51,082] Trial 77 finished with value: 0.6705043315571843 and parameters: {'n_estimators': 188, 'learning_rate': 0.25405001864614346, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 1.592417751058729, 'degree': 5, 'coef0': 0.6291303425648905}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:51,718] Trial 78 finished with value: 0.9489535935383199 and parameters: {'n_estimators': 148, 'learning_rate': 0.20184930543138635, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0930264745806801}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:52,130] Trial 79 finished with value: 0.8530369159459188 and parameters: {'n_estimators': 249, 'learning_rate': 0.3425617353986758, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.18880724810140742}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:52,324] Trial 80 finished with value: 0.8759702338461084 and parameters: {'n_estimators': 214, 'learning_rate': 0.28502977258205575, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:52,948] Trial 81 finished with value: 0.9432049461723968 and parameters: {'n_estimators': 154, 'learning_rate': 0.20123449299861937, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.1197804185074935}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:53,558] Trial 82 finished with value: 0.94320286269291 and parameters: {'n_estimators': 136, 'learning_rate': 0.244190328611221, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.424597717864778}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:54,092] Trial 83 finished with value: 0.9265953575750772 and parameters: {'n_estimators': 173, 'learning_rate': 0.2113131563444056, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.7751432908813656}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:54,385] Trial 84 finished with value: 0.9405676191829102 and parameters: {'n_estimators': 48, 'learning_rate': 0.1769465491916037, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.1317701234902864}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:55,155] Trial 85 finished with value: 0.9461117353464846 and parameters: {'n_estimators': 262, 'learning_rate': 0.3176795630787612, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 1.9190549701508972}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:55,764] Trial 86 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 193, 'learning_rate': 0.26419239924556914, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.768323929854739}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:55,888] Trial 87 finished with value: 0.8515658309121397 and parameters: {'n_estimators': 182, 'learning_rate': 0.2722479790329728, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 8.067883543139013}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:56,452] Trial 88 finished with value: 0.5249054202956112 and parameters: {'n_estimators': 201, 'learning_rate': 0.3660228120243797, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 2.5435597533944367, 'coef0': 0.1625403380559477}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:56,745] Trial 89 finished with value: 0.9353761797823182 and parameters: {'n_estimators': 217, 'learning_rate': 0.14050947729651117, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.082668135626794}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:57,414] Trial 90 finished with value: 0.9461914397690464 and parameters: {'n_estimators': 243, 'learning_rate': 0.40636575903125277, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1374915009572724}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:58,083] Trial 91 finished with value: 0.9433191177151397 and parameters: {'n_estimators': 137, 'learning_rate': 0.2050658999304865, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6514217851524977}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:58,822] Trial 92 finished with value: 0.9432909030357621 and parameters: {'n_estimators': 225, 'learning_rate': 0.2222123184480564, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.331241527111629}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:59,426] Trial 93 finished with value: 0.9488798569635867 and parameters: {'n_estimators': 164, 'learning_rate': 0.17279265207727196, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.9933659596849163}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:00,176] Trial 94 finished with value: 0.9461776790778822 and parameters: {'n_estimators': 268, 'learning_rate': 0.31518497467892653, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.201533416805354}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:00,537] Trial 95 finished with value: 0.9350713788373026 and parameters: {'n_estimators': 110, 'learning_rate': 0.2548250311872609, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.602537975876707}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:01,442] Trial 96 finished with value: 0.9428383837566567 and parameters: {'n_estimators': 197, 'learning_rate': 0.16383718909942865, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.74429116577557}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:02,495] Trial 97 finished with value: 0.6941801663418611 and parameters: {'n_estimators': 236, 'learning_rate': 0.19045988916497364, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 0.5507502417499932, 'degree': 3, 'coef0': 0.5212178203250792}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:02,893] Trial 98 finished with value: 0.9372552798787337 and parameters: {'n_estimators': 183, 'learning_rate': 0.2738956005721183, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 1.5112047541146179}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:03,158] Trial 99 finished with value: 0.8305296592545964 and parameters: {'n_estimators': 243, 'learning_rate': 0.22214604361651502, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.034548703205194466}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:03,330] Trial 100 finished with value: 0.8578592756814178 and parameters: {'n_estimators': 211, 'learning_rate': 0.33169917655289977, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:03,885] Trial 101 finished with value: 0.9377234617768158 and parameters: {'n_estimators': 157, 'learning_rate': 0.17626469712395465, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8986221438856852}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:04,576] Trial 102 finished with value: 0.9489822458261082 and parameters: {'n_estimators': 172, 'learning_rate': 0.293264685705061, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0710442197687955}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:05,435] Trial 103 finished with value: 0.8062559026857938 and parameters: {'n_estimators': 144, 'learning_rate': 0.010553067733616528, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.108454484699699}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:06,248] Trial 104 finished with value: 0.9432935743437543 and parameters: {'n_estimators': 226, 'learning_rate': 0.2975390616899621, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.1467167237895284}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:07,093] Trial 105 finished with value: 0.9518286923687628 and parameters: {'n_estimators': 192, 'learning_rate': 0.24331029503500007, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7495618454027402}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:08,068] Trial 106 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 204, 'learning_rate': 0.26097714815919504, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7638013611577343}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:08,885] Trial 107 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 205, 'learning_rate': 0.252142149886663, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6815108553353053}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:09,304] Trial 108 finished with value: 0.899160357207285 and parameters: {'n_estimators': 251, 'learning_rate': 0.5668562989797123, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.9079402572030912}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:09,341] Trial 109 finished with value: -inf and parameters: {'n_estimators': 193, 'learning_rate': 0.37388674256800275, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 6.342042428769567, 'coef0': 0.8508850801893877}. Best is trial 86 with value: 0.9573878203541313.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Trial failed with exception: \n", + "All the 10 fits failed.\n", + "It is very likely that your model is misconfigured.\n", + "You can try to debug the error by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/pipeline.py\", line 662, in fit\n", + " self._final_estimator.fit(Xt, y, **last_step_params[\"fit\"])\n", + " ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 628, in fit\n", + " return super().fit(training_data, y, sample_weight)\n", + " ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/ensemble/_weight_boosting.py\", line 167, in fit\n", + " sample_weight, estimator_weight, estimator_error = self._boost(\n", + " ~~~~~~~~~~~^\n", + " iboost, X, y, sample_weight, random_state\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 702, in _boost\n", + " raise ValueError(\n", + " \"BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\"\n", + " )\n", + "ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:03:09,683] Trial 110 finished with value: 0.9354204269132287 and parameters: {'n_estimators': 223, 'learning_rate': 0.11525970851531234, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.42390474054593}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:10,337] Trial 111 finished with value: 0.9432228758248777 and parameters: {'n_estimators': 184, 'learning_rate': 0.2319177796947066, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3285933571091035}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:10,826] Trial 112 finished with value: 0.9547394467306798 and parameters: {'n_estimators': 172, 'learning_rate': 0.45079109156398994, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.2893364126109446}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:11,421] Trial 113 finished with value: 0.9377302419765551 and parameters: {'n_estimators': 235, 'learning_rate': 0.44759844230443413, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7122505150670086}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:11,715] Trial 114 finished with value: 0.9321772059231634 and parameters: {'n_estimators': 202, 'learning_rate': 0.6764856671426681, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9871144590689882}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:12,580] Trial 115 finished with value: 0.9460809161475096 and parameters: {'n_estimators': 222, 'learning_rate': 0.26207999753938394, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1480447330624464}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:13,366] Trial 116 finished with value: 0.9488718056362714 and parameters: {'n_estimators': 163, 'learning_rate': 0.14775843924623255, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.388882471501774}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:13,630] Trial 117 finished with value: 0.9322849692738714 and parameters: {'n_estimators': 268, 'learning_rate': 0.5585942165767696, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6804771721860126}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:13,919] Trial 118 finished with value: 0.6905746692841864 and parameters: {'n_estimators': 243, 'learning_rate': 0.41799875124416175, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 3.3226800570154715, 'degree': 4, 'coef0': 0.3764539706641709}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:14,007] Trial 119 finished with value: 0.5473898159570962 and parameters: {'n_estimators': 213, 'learning_rate': 0.23662858855680907, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 8.081957798626714}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:14,460] Trial 120 finished with value: 0.9404654768430832 and parameters: {'n_estimators': 178, 'learning_rate': 0.19303072025137125, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.7206005729161484}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:15,334] Trial 121 finished with value: 0.9433827529207601 and parameters: {'n_estimators': 195, 'learning_rate': 0.27516173815741723, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.092849002219574}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:15,773] Trial 122 finished with value: 0.9433011880626585 and parameters: {'n_estimators': 169, 'learning_rate': 0.28751301328977386, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.2666489829518957}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:16,350] Trial 123 finished with value: 0.9489562648463121 and parameters: {'n_estimators': 206, 'learning_rate': 0.34002413096362905, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.791063939373234}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:17,309] Trial 124 finished with value: 0.948832689197155 and parameters: {'n_estimators': 231, 'learning_rate': 0.21115067056784395, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.552707016459578}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:17,630] Trial 125 finished with value: 0.8853569770206734 and parameters: {'n_estimators': 288, 'learning_rate': 0.2994230095220126, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.5219698007306968}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:17,858] Trial 126 finished with value: 0.9461482472660036 and parameters: {'n_estimators': 187, 'learning_rate': 0.7884721750296556, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.170239804867078}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:18,074] Trial 127 finished with value: 0.8714309902246997 and parameters: {'n_estimators': 126, 'learning_rate': 0.24054334690540302, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:18,548] Trial 128 finished with value: 0.9012734581578833 and parameters: {'n_estimators': 256, 'learning_rate': 0.38409733682042313, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.4191660723818265}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:18,872] Trial 129 finished with value: 0.9349763660408265 and parameters: {'n_estimators': 193, 'learning_rate': 0.47044486253274354, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0705422821711204}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:19,413] Trial 130 finished with value: 0.9434181820431042 and parameters: {'n_estimators': 176, 'learning_rate': 0.21850684780654933, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.5125467723090513}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:20,153] Trial 131 finished with value: 0.9460737251637724 and parameters: {'n_estimators': 206, 'learning_rate': 0.2531366441565206, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7267950905931142}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:20,897] Trial 132 finished with value: 0.9490707723468574 and parameters: {'n_estimators': 165, 'learning_rate': 0.18760740530924705, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.265656983620488}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:21,743] Trial 133 finished with value: 0.943311571394499 and parameters: {'n_estimators': 164, 'learning_rate': 0.19086079419695584, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.2097265572609297}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:22,476] Trial 134 finished with value: 0.9516409872982872 and parameters: {'n_estimators': 217, 'learning_rate': 0.29735193665249443, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.770599254653628}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:23,321] Trial 135 finished with value: 0.9517444082110016 and parameters: {'n_estimators': 218, 'learning_rate': 0.1632302131953216, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.040113453036413}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:24,014] Trial 136 finished with value: 0.9516815633204476 and parameters: {'n_estimators': 218, 'learning_rate': 0.16882720694545292, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.942970319501494}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:25,170] Trial 137 finished with value: -inf and parameters: {'n_estimators': 247, 'learning_rate': 0.1278287180708752, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 4.846425871954481, 'coef0': 0.25306830107690254}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:25,930] Trial 138 finished with value: 0.946129038490311 and parameters: {'n_estimators': 237, 'learning_rate': 0.10010032101446002, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.968090929872483}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:26,354] Trial 139 finished with value: 0.9463381854964412 and parameters: {'n_estimators': 231, 'learning_rate': 0.15840971565975542, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7352933426106074}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:27,210] Trial 140 finished with value: 0.9460938056940037 and parameters: {'n_estimators': 211, 'learning_rate': 0.17239197988266658, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3235504334453292}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:27,967] Trial 141 finished with value: 0.9487049848424336 and parameters: {'n_estimators': 219, 'learning_rate': 0.21300438495163315, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.790899376657866}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:28,731] Trial 142 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 219, 'learning_rate': 0.23442872811180468, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.6011804785275734}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:29,792] Trial 143 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 264, 'learning_rate': 0.20570915176817917, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8695111203697865}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:30,746] Trial 144 finished with value: 0.9374704190223566 and parameters: {'n_estimators': 195, 'learning_rate': 0.22711948376345956, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.417921813995831}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:31,517] Trial 145 finished with value: 0.9490205693199103 and parameters: {'n_estimators': 220, 'learning_rate': 0.1523444667474847, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.36120407727575}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:32,074] Trial 146 finished with value: 0.946030122496716 and parameters: {'n_estimators': 307, 'learning_rate': 0.24890881861731973, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.228147164535369}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:33,353] Trial 147 finished with value: 0.7023921951486901 and parameters: {'n_estimators': 251, 'learning_rate': 0.18049116357783734, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 2.1660641663421627, 'degree': 2, 'coef0': 0.5060218846433415}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:33,449] Trial 148 finished with value: 0.8791645618408939 and parameters: {'n_estimators': 227, 'learning_rate': 0.13354408856364375, 'algorithm': 'SAMME.R', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 5.979046347062491}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:33,784] Trial 149 finished with value: 0.9054841227029135 and parameters: {'n_estimators': 199, 'learning_rate': 0.16667582378735823, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.4840202886913443}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:34,114] Trial 150 finished with value: 0.9166507172958607 and parameters: {'n_estimators': 186, 'learning_rate': 0.26720591763623947, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.07839370990501919}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:34,758] Trial 151 finished with value: 0.9138729963208455 and parameters: {'n_estimators': 216, 'learning_rate': 0.2302042750507537, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1122679138806006}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:35,507] Trial 152 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 241, 'learning_rate': 0.31520505133488197, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.6944891555683936}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:36,306] Trial 153 finished with value: 0.9461636352536825 and parameters: {'n_estimators': 239, 'learning_rate': 0.3236701702197362, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9127662798338538}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:37,049] Trial 154 finished with value: 0.9462952708457747 and parameters: {'n_estimators': 207, 'learning_rate': 0.3535507455857343, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.58334971605361}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:37,463] Trial 155 finished with value: 0.9461336301867951 and parameters: {'n_estimators': 272, 'learning_rate': 0.5199391044125163, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.676357734051705}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:37,874] Trial 156 finished with value: 0.8602959645297137 and parameters: {'n_estimators': 258, 'learning_rate': 0.27012467250976774, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.0019893842962743474}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:38,092] Trial 157 finished with value: 0.8703560070298408 and parameters: {'n_estimators': 229, 'learning_rate': 0.20094439327024868, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:38,652] Trial 158 finished with value: 0.9435799175554489 and parameters: {'n_estimators': 248, 'learning_rate': 0.24458403490438416, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.4585405054559875}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:39,478] Trial 159 finished with value: 0.9519111763632015 and parameters: {'n_estimators': 206, 'learning_rate': 0.06428014850687971, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.5236712354238175}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:40,291] Trial 160 finished with value: 0.9462496595153113 and parameters: {'n_estimators': 182, 'learning_rate': 0.06148345147359303, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.511917074131766}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:41,296] Trial 161 finished with value: 0.9433997373083892 and parameters: {'n_estimators': 200, 'learning_rate': 0.056282449823456975, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9714411114029415}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:42,007] Trial 162 finished with value: 0.935001884879774 and parameters: {'n_estimators': 210, 'learning_rate': 0.06614387596029363, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7849457122146224}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:42,583] Trial 163 finished with value: 0.9460030266448959 and parameters: {'n_estimators': 223, 'learning_rate': 0.22164397237087538, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.232096588027822}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:43,298] Trial 164 finished with value: 0.9518914317907727 and parameters: {'n_estimators': 242, 'learning_rate': 0.08837430701870018, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.371958876189318}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:44,152] Trial 165 finished with value: 0.9461927188922579 and parameters: {'n_estimators': 238, 'learning_rate': 0.07360033276030915, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.639784254485829}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:45,001] Trial 166 finished with value: 0.9489818082176974 and parameters: {'n_estimators': 254, 'learning_rate': 0.07908133007358858, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.219443385176234}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:45,325] Trial 167 finished with value: 0.9211705188978586 and parameters: {'n_estimators': 189, 'learning_rate': 0.6303367464202104, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.3593735751901277}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:46,049] Trial 168 finished with value: 0.5371120525831441 and parameters: {'n_estimators': 242, 'learning_rate': 0.3106508834294839, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 1.809149011162188, 'coef0': 0.9029906019159136}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:46,522] Trial 169 finished with value: 0.9351877596174386 and parameters: {'n_estimators': 231, 'learning_rate': 0.10364929586198274, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.572489372413239}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:47,500] Trial 170 finished with value: 0.9432840356506091 and parameters: {'n_estimators': 205, 'learning_rate': 0.08771082293345642, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.4686214773634303}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:48,332] Trial 171 finished with value: 0.9462224888474111 and parameters: {'n_estimators': 218, 'learning_rate': 0.23476923003084876, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.830028745713152}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:49,452] Trial 172 finished with value: 0.8773099501946401 and parameters: {'n_estimators': 225, 'learning_rate': 0.06587675146124812, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.016926388284853246}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:49,750] Trial 173 finished with value: 0.9265768775169478 and parameters: {'n_estimators': 197, 'learning_rate': 0.2652275469166709, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8718946130665782}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:50,409] Trial 174 finished with value: 0.9544099308018232 and parameters: {'n_estimators': 280, 'learning_rate': 0.19683229184220954, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2028559208805314}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:51,383] Trial 175 finished with value: 0.9490737209676066 and parameters: {'n_estimators': 281, 'learning_rate': 0.09276801286379756, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.0247920489149362}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:51,733] Trial 176 finished with value: 0.9297117181894698 and parameters: {'n_estimators': 263, 'learning_rate': 0.19306420905714758, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.146986179162074}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:52,924] Trial 177 finished with value: 0.9488718056362714 and parameters: {'n_estimators': 272, 'learning_rate': 0.21075557604381384, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4622172042445536}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:53,812] Trial 178 finished with value: 0.6905746692841864 and parameters: {'n_estimators': 242, 'learning_rate': 0.2472431025104272, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 3.4858813896883194, 'degree': 4, 'coef0': 0.09340899873225705}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:54,022] Trial 179 finished with value: 0.9347568931622089 and parameters: {'n_estimators': 254, 'learning_rate': 0.21538600767079638, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 1.7390434014906178}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:55,197] Trial 180 finished with value: 0.9405344311859402 and parameters: {'n_estimators': 294, 'learning_rate': 0.0476544362356825, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.2260991184797905}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:55,869] Trial 181 finished with value: 0.9490340875605312 and parameters: {'n_estimators': 231, 'learning_rate': 0.181870970871893, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.992069313948637}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:56,653] Trial 182 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 213, 'learning_rate': 0.27280377214301693, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.387474281739788}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:57,258] Trial 183 finished with value: 0.943466304385906 and parameters: {'n_estimators': 205, 'learning_rate': 0.2020747222080973, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.149925894026264}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:57,925] Trial 184 finished with value: 0.9461317097983033 and parameters: {'n_estimators': 191, 'learning_rate': 0.1618939225574238, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.8537724728291467}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:58,667] Trial 185 finished with value: 0.9546584631849069 and parameters: {'n_estimators': 388, 'learning_rate': 0.23172077548387995, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.305222179127677}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:00,019] Trial 186 finished with value: 0.9236047324399677 and parameters: {'n_estimators': 246, 'learning_rate': 0.015120439714314308, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 2.1574976046467467}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:00,646] Trial 187 finished with value: 0.943202024996045 and parameters: {'n_estimators': 395, 'learning_rate': 0.2901873392685005, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.6327993424719893}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:02,156] Trial 188 finished with value: 0.9488691343282791 and parameters: {'n_estimators': 413, 'learning_rate': 0.23690288538405274, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9085381101542886}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:02,341] Trial 189 finished with value: 0.8768186259315769 and parameters: {'n_estimators': 347, 'learning_rate': 0.2249297866113301, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:03,570] Trial 190 finished with value: 0.9463066895734725 and parameters: {'n_estimators': 363, 'learning_rate': 0.24692399743713445, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 4.70397135863975}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:04,467] Trial 191 finished with value: 0.9517125575717025 and parameters: {'n_estimators': 405, 'learning_rate': 0.18927762197960674, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.0371730069380747}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:05,529] Trial 192 finished with value: 0.957290655564415 and parameters: {'n_estimators': 391, 'learning_rate': 0.186134731096261, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1592388038658434}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:05,912] Trial 193 finished with value: 0.9195083329662423 and parameters: {'n_estimators': 377, 'learning_rate': 0.26404661468696655, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.14635960598805775}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:06,997] Trial 194 finished with value: 0.951698100788148 and parameters: {'n_estimators': 389, 'learning_rate': 0.21110976555505545, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4076903818873254}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:07,849] Trial 195 finished with value: 0.9462224888474111 and parameters: {'n_estimators': 383, 'learning_rate': 0.29013599820311725, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7990081861455174}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:08,719] Trial 196 finished with value: 0.951896719579647 and parameters: {'n_estimators': 397, 'learning_rate': 0.07357902059935685, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.5500892801338229}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:09,593] Trial 197 finished with value: 0.954692128744154 and parameters: {'n_estimators': 397, 'learning_rate': 0.0743400250121961, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.439866900092313}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:10,153] Trial 198 finished with value: 0.9407596316566416 and parameters: {'n_estimators': 418, 'learning_rate': 0.07062926587315435, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.3067035030172236}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:10,880] Trial 199 finished with value: 0.9519222629510324 and parameters: {'n_estimators': 405, 'learning_rate': 0.07803729201336104, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.4508904105515619}. Best is trial 86 with value: 0.9573878203541313.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", "Best trial:\n", - "F1 Score: 0.7583125868901313\n", - "Parameters: \n", - "n_estimators: 384\n", - "learning_rate: 0.06667610599938725\n", - "algorithm: SAMME\n", - "scaler: robust\n", - "kernel: rbf\n", - "gamma: 0.002777056559327566\n" + " Value (F1 Score): 0.9574\n", + " Parameters: \n", + " n_estimators: 193\n", + " learning_rate: 0.26419239924556914\n", + " algorithm: SAMME\n", + " scaler: minmax\n", + " kernel: rbf\n", + " gamma: 2.768323929854739\n" ] } ], "source": [ "import optuna\n", "import numpy as np\n", + "\n", "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", + "from sklearn.preprocessing import OneHotEncoder\n", + "from sklearn.compose import ColumnTransformer, make_column_selector\n", + "from sklearn.pipeline import Pipeline\n", + "\n", + "# X, y assumed pre-defined (raw, with object/category cols intact)\n", "\n", "\n", "def custom_loss(y_true, y_pred, weights):\n", " return np.mean(weights * (y_true - y_pred) ** 2)\n", "\n", "\n", - "df = X\n", - "\n", - "# One-hot encoding\n", - "cat_features = list(df.select_dtypes(include=[\"object\", \"category\"]).columns)\n", - "for col in cat_features:\n", - " df_onehot = pd.get_dummies(df[col], prefix=col)\n", - " df = df.drop(col, axis=1)\n", - " df = pd.concat([df_onehot, df], axis=1)\n", + "def _make_preprocessor() -> ColumnTransformer:\n", + " \"\"\"\n", + " Creates a preprocessor that only one-hot encodes categorical features\n", + " and passes numerical features through without scaling.\n", + " \"\"\"\n", + " return ColumnTransformer(\n", + " transformers=[\n", + " # The \"cat\" transformer applies OneHotEncoder to columns of type object or category.\n", + " (\n", + " \"cat\",\n", + " OneHotEncoder(handle_unknown=\"ignore\"),\n", + " make_column_selector(dtype_include=[\"object\", \"category\"]),\n", + " ),\n", + " ],\n", + " # 'remainder=\"passthrough\"' ensures that all other columns (i.e., numerical ones) are kept.\n", + " remainder=\"passthrough\",\n", + " n_jobs=None,\n", + " )\n", "\n", "\n", "def objective(trial):\n", + " \"\"\"\n", + " Optuna objective function for hyperparameter tuning.\n", + " \"\"\"\n", + " # Define the search space for the classifier's parameters.\n", + " # The \"scaler\" parameter has been removed.\n", " params = {\n", " \"n_estimators\": trial.suggest_int(\"n_estimators\", 10, 500),\n", " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 1.0, log=True),\n", @@ -184,7 +523,7 @@ " \"kernel\", [\"linear\", \"rbf\", \"poly\", \"sigmoid\"]\n", " ),\n", " }\n", - "\n", + " # Conditionally add parameters based on the chosen kernel.\n", " if params[\"kernel\"] != \"linear\":\n", " params[\"gamma\"] = trial.suggest_float(\"gamma\", 1e-3, 10.0, log=True)\n", " if params[\"kernel\"] == \"poly\":\n", @@ -192,34 +531,39 @@ " if params[\"kernel\"] in [\"poly\", \"sigmoid\"]:\n", " params[\"coef0\"] = trial.suggest_float(\"coef0\", 0.0, 1.0)\n", "\n", - " # Using a custom loss function here\n", - " # params['loss_function'] = custom_loss\n", + " # Build a leakage-free pipeline for the trial.\n", + " # The preprocessor no longer requires a scaler argument.\n", + " pre = _make_preprocessor()\n", "\n", - " model = LinearBoostClassifier(**params)\n", + " # All items in `params` are now intended for the classifier.\n", + " clf = LinearBoostClassifier(**params)\n", "\n", - " scores = cross_val_score(\n", - " estimator=model,\n", - " X=df,\n", - " y=y,\n", - " scoring=\"f1_weighted\",\n", - " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", - " )\n", + " pipe = Pipeline(steps=[(\"preprocess\", pre), (\"model\", clf)])\n", "\n", - " return scores.mean()\n", + " try:\n", + " # Perform stratified 10-fold cross-validation.\n", + " cv = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n", + " scores = cross_val_score(pipe, X, y, scoring=\"f1_weighted\", cv=cv)\n", + " # Return the mean F1 score, or negative infinity if scores contain NaN.\n", + " return -np.inf if np.isnan(scores).any() else scores.mean()\n", + " except Exception as e:\n", + " # Prune trial if an exception occurs (e.g., invalid parameter combination).\n", + " print(f\"Trial failed with exception: {e}\")\n", + " return -np.inf\n", "\n", "\n", - "# Create an Optuna study and optimize the objective function\n", + "# --- Optuna Study Execution ---\n", + "# Create a study object and specify the direction as \"maximize\" for F1 score.\n", "study = optuna.create_study(direction=\"maximize\")\n", "study.optimize(objective, n_trials=200)\n", "\n", - "# Display the best trial's results\n", - "print(\"Best trial:\")\n", - "trial = study.best_trial\n", - "\n", - "print(f\"F1 Score: {trial.value}\")\n", - "print(\"Parameters: \")\n", - "for key, value in trial.params.items():\n", - " print(f\"{key}: {value}\")" + "# --- Print Best Results ---\n", + "print(\"\\nBest trial:\")\n", + "best_trial = study.best_trial\n", + "print(f\" Value (F1 Score): {best_trial.value:.4f}\")\n", + "print(\" Parameters: \")\n", + "for key, value in best_trial.params.items():\n", + " print(f\" {key}: {value}\")" ] }, { @@ -238,11 +582,207 @@ "name": "stderr", "output_type": "stream", "text": [ - "[I 2025-07-28 20:34:58,357] A new study created in memory with name: no-name-fd2e9753-4f61-49f9-a22c-28b4c0177247\n", - "[I 2025-07-28 20:34:59,157] Trial 0 finished with value: 0.653658178784821 and parameters: {'n_estimators': 122, 'max_depth': 18, 'learning_rate': 0.6638400324564625, 'gamma': 1.3755330590290604e-05, 'min_child_weight': 6, 'subsample': 0.5447494156166959, 'colsample_bytree': 0.8879793066877644, 'reg_alpha': 1.0163427568069608e-07, 'reg_lambda': 2.39079916775675e-06}. Best is trial 0 with value: 0.653658178784821.\n", - "[I 2025-07-28 20:34:59,681] Trial 1 finished with value: 0.6770776702365993 and parameters: {'n_estimators': 317, 'max_depth': 20, 'learning_rate': 0.13249519981914618, 'gamma': 1.5953454630407348e-08, 'min_child_weight': 8, 'subsample': 0.9709077195029082, 'colsample_bytree': 0.9624785240081783, 'reg_alpha': 2.203094364625466e-07, 'reg_lambda': 1.4395372969777643e-08}. Best is trial 1 with value: 0.6770776702365993.\n", - "...", - "[I 2025-07-28 20:35:10,555] Trial 199 finished with value: 0.716699568607657 and parameters: {'n_estimators': 736, 'max_depth': 14, 'learning_rate': 0.5430003212800782, 'gamma': 0.00012981585330188922, 'min_child_weight': 7, 'subsample': 0.988996549758597, 'colsample_bytree': 0.5778156428539348, 'reg_alpha': 0.0012464630655151046, 'reg_lambda': 0.00018326860521084625}. Best is trial 22 with value: 0.7218094394645215.\n" + "[I 2025-08-18 23:04:37,538] A new study created in memory with name: no-name-a6ac08d4-0166-4e55-82db-e34c20f65e38\n", + "[I 2025-08-18 23:04:38,723] Trial 0 finished with value: 0.9636743691091517 and parameters: {'n_estimators': 793, 'max_depth': 16, 'learning_rate': 0.08966826500844771, 'gamma': 1.5332174950801975e-05, 'min_child_weight': 7, 'subsample': 0.8206767596857434, 'colsample_bytree': 0.5726809729609164, 'reg_alpha': 0.3000662922036043, 'reg_lambda': 6.694076855447791e-06}. Best is trial 0 with value: 0.9636743691091517.\n", + "[I 2025-08-18 23:04:39,297] Trial 1 finished with value: 0.92515962298571 and parameters: {'n_estimators': 363, 'max_depth': 1, 'learning_rate': 0.6923884519284504, 'gamma': 2.3719556857557514e-07, 'min_child_weight': 9, 'subsample': 0.5195696271131344, 'colsample_bytree': 0.9721890311504119, 'reg_alpha': 0.0004982860931446735, 'reg_lambda': 4.9598622967800296e-08}. Best is trial 0 with value: 0.9636743691091517.\n", + "[I 2025-08-18 23:04:39,907] Trial 2 finished with value: 0.9660813823857302 and parameters: {'n_estimators': 765, 'max_depth': 19, 'learning_rate': 0.03328962689146766, 'gamma': 0.005416426649707568, 'min_child_weight': 5, 'subsample': 0.8716669106394426, 'colsample_bytree': 0.619605690338052, 'reg_alpha': 0.1588033011486252, 'reg_lambda': 0.10090421373216449}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:39,956] Trial 3 finished with value: 0.9646701124961995 and parameters: {'n_estimators': 162, 'max_depth': 14, 'learning_rate': 0.22096268147375914, 'gamma': 0.20303915469434114, 'min_child_weight': 3, 'subsample': 0.7816550027087239, 'colsample_bytree': 0.9440324292952285, 'reg_alpha': 0.00019615793084263862, 'reg_lambda': 0.00012620616546111783}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,531] Trial 4 finished with value: 0.9618906455862977 and parameters: {'n_estimators': 746, 'max_depth': 5, 'learning_rate': 0.27373124279594174, 'gamma': 5.113866726169806e-07, 'min_child_weight': 8, 'subsample': 0.9786346051499656, 'colsample_bytree': 0.817382203507034, 'reg_alpha': 0.00010865601540579662, 'reg_lambda': 0.7028348077651659}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,571] Trial 5 finished with value: 0.9375772777946689 and parameters: {'n_estimators': 131, 'max_depth': 9, 'learning_rate': 0.6666830358877334, 'gamma': 2.3337802367945706e-06, 'min_child_weight': 10, 'subsample': 0.5767815340215819, 'colsample_bytree': 0.8847564080638974, 'reg_alpha': 1.1720116806607218e-05, 'reg_lambda': 0.00014985518222546636}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,647] Trial 6 finished with value: 0.9322793148880105 and parameters: {'n_estimators': 811, 'max_depth': 19, 'learning_rate': 0.6284423078537571, 'gamma': 2.5468120149201276e-08, 'min_child_weight': 8, 'subsample': 0.5241240142259422, 'colsample_bytree': 0.7077124133325703, 'reg_alpha': 0.00122899449385656, 'reg_lambda': 4.150700737033019e-05}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,675] Trial 7 finished with value: 0.9404048849701023 and parameters: {'n_estimators': 55, 'max_depth': 8, 'learning_rate': 0.6143004867698488, 'gamma': 0.0013027026334781191, 'min_child_weight': 7, 'subsample': 0.6231620588280503, 'colsample_bytree': 0.8828670937564691, 'reg_alpha': 2.9404686235297146e-07, 'reg_lambda': 3.754444639692557e-06}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,740] Trial 8 finished with value: 0.9578595317725753 and parameters: {'n_estimators': 499, 'max_depth': 18, 'learning_rate': 0.5646291569978734, 'gamma': 1.7349709546981462e-05, 'min_child_weight': 2, 'subsample': 0.8928178421726397, 'colsample_bytree': 0.6848598778618181, 'reg_alpha': 0.5610745294606653, 'reg_lambda': 0.5364150960157834}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,805] Trial 9 finished with value: 0.9590174318435187 and parameters: {'n_estimators': 699, 'max_depth': 4, 'learning_rate': 0.31764392327897784, 'gamma': 0.11453542510872944, 'min_child_weight': 10, 'subsample': 0.7055074511257982, 'colsample_bytree': 0.796546556661627, 'reg_alpha': 2.907763331398582e-05, 'reg_lambda': 2.2504856133119337e-05}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,963] Trial 10 finished with value: 0.9670897942637072 and parameters: {'n_estimators': 972, 'max_depth': 13, 'learning_rate': 0.02160073099534278, 'gamma': 0.0012263645582748532, 'min_child_weight': 4, 'subsample': 0.9792412216883989, 'colsample_bytree': 0.520612587086734, 'reg_alpha': 0.013660705792304169, 'reg_lambda': 0.011791232435673288}. Best is trial 10 with value: 0.9670897942637072.\n", + "[I 2025-08-18 23:04:41,107] Trial 11 finished with value: 0.9643077936556198 and parameters: {'n_estimators': 950, 'max_depth': 12, 'learning_rate': 0.02786001957318099, 'gamma': 0.0017314307200539348, 'min_child_weight': 4, 'subsample': 0.9907050379036834, 'colsample_bytree': 0.5125919786788546, 'reg_alpha': 0.01547481122556199, 'reg_lambda': 0.021894838205846742}. Best is trial 10 with value: 0.9670897942637072.\n", + "[I 2025-08-18 23:04:41,213] Trial 12 finished with value: 0.9663930272625926 and parameters: {'n_estimators': 993, 'max_depth': 20, 'learning_rate': 0.14543560489328874, 'gamma': 0.0033996503304433074, 'min_child_weight': 5, 'subsample': 0.8889007946941537, 'colsample_bytree': 0.6084715786342512, 'reg_alpha': 0.022413404033686066, 'reg_lambda': 0.011064527798418372}. Best is trial 10 with value: 0.9670897942637072.\n", + "[I 2025-08-18 23:04:41,322] Trial 13 finished with value: 0.968164082294517 and parameters: {'n_estimators': 955, 'max_depth': 14, 'learning_rate': 0.1639284511998979, 'gamma': 0.0002751891194586191, 'min_child_weight': 1, 'subsample': 0.9147497384875082, 'colsample_bytree': 0.5126649768955113, 'reg_alpha': 0.016597036392593374, 'reg_lambda': 0.004707104171200651}. Best is trial 13 with value: 0.968164082294517.\n", + "[I 2025-08-18 23:04:41,408] Trial 14 finished with value: 0.9720735785953177 and parameters: {'n_estimators': 635, 'max_depth': 12, 'learning_rate': 0.44435309051067096, 'gamma': 0.0006644642045654169, 'min_child_weight': 1, 'subsample': 0.9432618865143836, 'colsample_bytree': 0.5039154540738406, 'reg_alpha': 0.004876635115949546, 'reg_lambda': 0.0064355512337324105}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,484] Trial 15 finished with value: 0.9674521131042871 and parameters: {'n_estimators': 569, 'max_depth': 10, 'learning_rate': 0.43787269752034375, 'gamma': 0.00011195314945572638, 'min_child_weight': 1, 'subsample': 0.7069629644516782, 'colsample_bytree': 0.5634075101229923, 'reg_alpha': 4.464784207396974e-08, 'reg_lambda': 0.003997182136400165}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,558] Trial 16 finished with value: 0.9707433870477349 and parameters: {'n_estimators': 370, 'max_depth': 15, 'learning_rate': 0.4599427117745171, 'gamma': 8.735091706299628e-05, 'min_child_weight': 1, 'subsample': 0.9257669635457493, 'colsample_bytree': 0.6689607583849055, 'reg_alpha': 0.003005669831594476, 'reg_lambda': 0.0009691828324956179}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,631] Trial 17 finished with value: 0.9679563190432756 and parameters: {'n_estimators': 336, 'max_depth': 16, 'learning_rate': 0.4272808911789559, 'gamma': 1.1267461214053029e-05, 'min_child_weight': 2, 'subsample': 0.8380523208836226, 'colsample_bytree': 0.672358753892155, 'reg_alpha': 3.5941246015085105e-06, 'reg_lambda': 0.0012762246601831144}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,703] Trial 18 finished with value: 0.962460727678119 and parameters: {'n_estimators': 412, 'max_depth': 7, 'learning_rate': 0.4945841962092967, 'gamma': 0.7046722512199631, 'min_child_weight': 2, 'subsample': 0.9443084841264685, 'colsample_bytree': 0.752150502842086, 'reg_alpha': 0.0022930157034841687, 'reg_lambda': 0.0005914759736460705}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,781] Trial 19 finished with value: 0.9693523867436911 and parameters: {'n_estimators': 603, 'max_depth': 11, 'learning_rate': 0.4182386109054242, 'gamma': 0.02844656967423761, 'min_child_weight': 3, 'subsample': 0.7636043135868457, 'colsample_bytree': 0.6293491016063527, 'reg_alpha': 0.002891811181173915, 'reg_lambda': 6.079751271976952e-07}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,844] Trial 20 finished with value: 0.9646321070234114 and parameters: {'n_estimators': 263, 'max_depth': 16, 'learning_rate': 0.5343710663782837, 'gamma': 0.00020994204354847013, 'min_child_weight': 1, 'subsample': 0.933551117358393, 'colsample_bytree': 0.7553892763360576, 'reg_alpha': 1.4227453672543946e-06, 'reg_lambda': 0.07295757354368651}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,929] Trial 21 finished with value: 0.9683287726765988 and parameters: {'n_estimators': 618, 'max_depth': 11, 'learning_rate': 0.39203875257523096, 'gamma': 0.020660444962692592, 'min_child_weight': 3, 'subsample': 0.7522258388072962, 'colsample_bytree': 0.6287497031716449, 'reg_alpha': 0.0027780793331277473, 'reg_lambda': 4.744211463091777e-07}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,003] Trial 22 finished with value: 0.9650729705077531 and parameters: {'n_estimators': 479, 'max_depth': 11, 'learning_rate': 0.4816697063234048, 'gamma': 0.02294520899250463, 'min_child_weight': 3, 'subsample': 0.8261862173185567, 'colsample_bytree': 0.6535905438209455, 'reg_alpha': 0.05648104038500446, 'reg_lambda': 7.945709365351044e-08}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,087] Trial 23 finished with value: 0.9649690888821322 and parameters: {'n_estimators': 617, 'max_depth': 14, 'learning_rate': 0.35399121863614574, 'gamma': 0.023886459668739847, 'min_child_weight': 1, 'subsample': 0.6707746880436944, 'colsample_bytree': 0.5755080172718738, 'reg_alpha': 0.004076372892245553, 'reg_lambda': 9.163582970819522e-07}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,163] Trial 24 finished with value: 0.9611761426978817 and parameters: {'n_estimators': 443, 'max_depth': 12, 'learning_rate': 0.3139681715812469, 'gamma': 0.0003768107966552948, 'min_child_weight': 2, 'subsample': 0.785577063811775, 'colsample_bytree': 0.7035064694391241, 'reg_alpha': 0.0002961952288355031, 'reg_lambda': 0.0007189349722448769}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,226] Trial 25 finished with value: 0.9621769534813012 and parameters: {'n_estimators': 270, 'max_depth': 17, 'learning_rate': 0.46661524082093503, 'gamma': 3.724723823557411e-05, 'min_child_weight': 4, 'subsample': 0.8543235968447394, 'colsample_bytree': 0.5745613732539564, 'reg_alpha': 5.043186797452251e-05, 'reg_lambda': 1.0823805710576936e-08}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,310] Trial 26 finished with value: 0.967454646802473 and parameters: {'n_estimators': 571, 'max_depth': 7, 'learning_rate': 0.39555431045443845, 'gamma': 0.010531397617842813, 'min_child_weight': 3, 'subsample': 0.9520895450331223, 'colsample_bytree': 0.6505146452181498, 'reg_alpha': 0.07277660854823283, 'reg_lambda': 0.00017848811714192225}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,407] Trial 27 finished with value: 0.971115840681058 and parameters: {'n_estimators': 886, 'max_depth': 15, 'learning_rate': 0.5596905359749961, 'gamma': 0.109957517842398, 'min_child_weight': 1, 'subsample': 0.911463740843732, 'colsample_bytree': 0.7242482520459889, 'reg_alpha': 0.004304571005570774, 'reg_lambda': 0.0019289290476947067}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,567] Trial 28 finished with value: 0.9622124252559034 and parameters: {'n_estimators': 856, 'max_depth': 15, 'learning_rate': 0.5491779113793174, 'gamma': 0.9394863827667955, 'min_child_weight': 1, 'subsample': 0.9085194590375377, 'colsample_bytree': 0.8008991430166865, 'reg_alpha': 0.0007901559140269053, 'reg_lambda': 0.0017254433653291876}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,670] Trial 29 finished with value: 0.9647359886490323 and parameters: {'n_estimators': 862, 'max_depth': 17, 'learning_rate': 0.5820996718221064, 'gamma': 5.022199051728779e-06, 'min_child_weight': 6, 'subsample': 0.8071126403433657, 'colsample_bytree': 0.8688765430232145, 'reg_alpha': 0.6743398600163427, 'reg_lambda': 0.07862706605671561}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,758] Trial 30 finished with value: 0.9642292490118578 and parameters: {'n_estimators': 709, 'max_depth': 13, 'learning_rate': 0.5155202664068682, 'gamma': 5.8451733953677565e-05, 'min_child_weight': 2, 'subsample': 0.9509763250842893, 'colsample_bytree': 0.7129940865613236, 'reg_alpha': 0.008859259561073272, 'reg_lambda': 3.4509898100450316e-05}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,845] Trial 31 finished with value: 0.9657722712070538 and parameters: {'n_estimators': 668, 'max_depth': 10, 'learning_rate': 0.4395334552771406, 'gamma': 0.12712718293414763, 'min_child_weight': 1, 'subsample': 0.9988158980266512, 'colsample_bytree': 0.5936405830531623, 'reg_alpha': 0.004952419311036929, 'reg_lambda': 6.401818643223202e-06}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,919] Trial 32 finished with value: 0.961406709232796 and parameters: {'n_estimators': 566, 'max_depth': 15, 'learning_rate': 0.3597185445003348, 'gamma': 0.052315813645452125, 'min_child_weight': 2, 'subsample': 0.861533388856762, 'colsample_bytree': 0.5482756215722395, 'reg_alpha': 0.0008797977184427369, 'reg_lambda': 0.000414443174592793}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,983] Trial 33 finished with value: 0.9657722712070539 and parameters: {'n_estimators': 356, 'max_depth': 12, 'learning_rate': 0.5063187891048766, 'gamma': 0.0006293033474033146, 'min_child_weight': 3, 'subsample': 0.9245516224148534, 'colsample_bytree': 0.7700173552170951, 'reg_alpha': 0.1375518302261409, 'reg_lambda': 0.0033261674432578194}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,056] Trial 34 finished with value: 0.9628433161041858 and parameters: {'n_estimators': 281, 'max_depth': 15, 'learning_rate': 0.39986529526862014, 'gamma': 0.33270406488078025, 'min_child_weight': 1, 'subsample': 0.8777255486034471, 'colsample_bytree': 0.6377133084935319, 'reg_alpha': 0.00040666270333044826, 'reg_lambda': 0.01722992299278233}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,143] Trial 35 finished with value: 0.9677789601702645 and parameters: {'n_estimators': 809, 'max_depth': 13, 'learning_rate': 0.5932469392267316, 'gamma': 0.006088499877130821, 'min_child_weight': 2, 'subsample': 0.7328484494819534, 'colsample_bytree': 0.7319378460341505, 'reg_alpha': 0.05604671729670822, 'reg_lambda': 0.00026653903767523407}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,242] Trial 36 finished with value: 0.9578975372453634 and parameters: {'n_estimators': 894, 'max_depth': 17, 'learning_rate': 0.6747312199854105, 'gamma': 1.4778405111109977e-06, 'min_child_weight': 4, 'subsample': 0.8061783788836056, 'colsample_bytree': 0.6785763400584698, 'reg_alpha': 0.00011687995768555662, 'reg_lambda': 0.23451609747860863}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,305] Trial 37 finished with value: 0.9607327455153543 and parameters: {'n_estimators': 416, 'max_depth': 1, 'learning_rate': 0.4620319359751538, 'gamma': 0.060081915589133755, 'min_child_weight': 3, 'subsample': 0.9671673389437769, 'colsample_bytree': 0.5439077141472997, 'reg_alpha': 0.0016050980147079938, 'reg_lambda': 0.03470161515812803}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,391] Trial 38 finished with value: 0.9623315090706395 and parameters: {'n_estimators': 741, 'max_depth': 9, 'learning_rate': 0.26537466239492763, 'gamma': 3.8588922199082426e-08, 'min_child_weight': 6, 'subsample': 0.6229188943554498, 'colsample_bytree': 0.8482038406619968, 'reg_alpha': 0.005961031499798193, 'reg_lambda': 9.178673123098809e-05}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,453] Trial 39 finished with value: 0.9733835005574136 and parameters: {'n_estimators': 174, 'max_depth': 9, 'learning_rate': 0.3415861867273047, 'gamma': 0.00320158129516171, 'min_child_weight': 1, 'subsample': 0.7657875222614208, 'colsample_bytree': 0.6055391800615106, 'reg_alpha': 0.1961144247885326, 'reg_lambda': 1.3349872128243998e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,528] Trial 40 finished with value: 0.968103273538056 and parameters: {'n_estimators': 194, 'max_depth': 5, 'learning_rate': 0.2308941510629727, 'gamma': 0.002267995615949968, 'min_child_weight': 1, 'subsample': 0.907878075061457, 'colsample_bytree': 0.9968707460456452, 'reg_alpha': 0.18618906668818894, 'reg_lambda': 1.9657102325946478e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,569] Trial 41 finished with value: 0.9706876456876458 and parameters: {'n_estimators': 26, 'max_depth': 9, 'learning_rate': 0.3394366537016498, 'gamma': 0.0075177253863414695, 'min_child_weight': 2, 'subsample': 0.7720455412614378, 'colsample_bytree': 0.607113034664798, 'reg_alpha': 0.02755418326100873, 'reg_lambda': 1.6417879593738852e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,622] Trial 42 finished with value: 0.9656278504104592 and parameters: {'n_estimators': 28, 'max_depth': 8, 'learning_rate': 0.3375467490973728, 'gamma': 0.008183578589292693, 'min_child_weight': 2, 'subsample': 0.7841595414778176, 'colsample_bytree': 0.6001413581900443, 'reg_alpha': 0.039635394071934116, 'reg_lambda': 1.820175490207568e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,686] Trial 43 finished with value: 0.9674166413296849 and parameters: {'n_estimators': 92, 'max_depth': 9, 'learning_rate': 0.2951892312329311, 'gamma': 0.0011926871557951385, 'min_child_weight': 1, 'subsample': 0.7243233789331518, 'colsample_bytree': 0.6690830197165509, 'reg_alpha': 0.2981096546445941, 'reg_lambda': 1.4732474336111884e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,737] Trial 44 finished with value: 0.9664665045099827 and parameters: {'n_estimators': 176, 'max_depth': 3, 'learning_rate': 0.3778692466816108, 'gamma': 0.0006795734196391805, 'min_child_weight': 2, 'subsample': 0.846170946192214, 'colsample_bytree': 0.5421093232735782, 'reg_alpha': 0.1171370589737971, 'reg_lambda': 9.218742520129267e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,790] Trial 45 finished with value: 0.9642292490118578 and parameters: {'n_estimators': 112, 'max_depth': 6, 'learning_rate': 0.26260487033994784, 'gamma': 0.00011851832743201036, 'min_child_weight': 1, 'subsample': 0.670336459772904, 'colsample_bytree': 0.7208950473295055, 'reg_alpha': 0.02908781781480345, 'reg_lambda': 6.543787850283628e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,852] Trial 46 finished with value: 0.96029948312557 and parameters: {'n_estimators': 220, 'max_depth': 9, 'learning_rate': 0.6312256464453558, 'gamma': 0.0036712637572776517, 'min_child_weight': 1, 'subsample': 0.8759520439984964, 'colsample_bytree': 0.6914986554072519, 'reg_alpha': 0.3474285764344179, 'reg_lambda': 0.006752518206121544}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,904] Trial 47 finished with value: 0.9499163879598662 and parameters: {'n_estimators': 146, 'max_depth': 19, 'learning_rate': 0.20922691721035272, 'gamma': 3.8419590657259207e-05, 'min_child_weight': 8, 'subsample': 0.5049535044393377, 'colsample_bytree': 0.9226368889131558, 'reg_alpha': 0.010213751761400837, 'reg_lambda': 0.0014363034008709101}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,969] Trial 48 finished with value: 0.9649412182020877 and parameters: {'n_estimators': 64, 'max_depth': 8, 'learning_rate': 0.07577872858481222, 'gamma': 0.2638175764876564, 'min_child_weight': 2, 'subsample': 0.963968884483731, 'colsample_bytree': 0.5924098530493901, 'reg_alpha': 0.999637524746841, 'reg_lambda': 2.0261391177441924e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,033] Trial 49 finished with value: 0.9655645079558124 and parameters: {'n_estimators': 318, 'max_depth': 14, 'learning_rate': 0.33052174325673006, 'gamma': 0.011942467037248633, 'min_child_weight': 1, 'subsample': 0.6627788600351412, 'colsample_bytree': 0.6141066675957493, 'reg_alpha': 0.021696432447302145, 'reg_lambda': 1.0007983816416382e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,088] Trial 50 finished with value: 0.9663803587716633 and parameters: {'n_estimators': 236, 'max_depth': 10, 'learning_rate': 0.45078154977126994, 'gamma': 1.5117023515346045e-05, 'min_child_weight': 2, 'subsample': 0.5688408997309418, 'colsample_bytree': 0.5299284944128524, 'reg_alpha': 1.8494068989589203e-08, 'reg_lambda': 0.0022820773871882346}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,161] Trial 51 finished with value: 0.9703557312252965 and parameters: {'n_estimators': 512, 'max_depth': 11, 'learning_rate': 0.5295370440664156, 'gamma': 0.06319050293389655, 'min_child_weight': 3, 'subsample': 0.7545681529668761, 'colsample_bytree': 0.6317023972454394, 'reg_alpha': 0.0015414355079223494, 'reg_lambda': 4.324091704580854e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,237] Trial 52 finished with value: 0.9709663524880916 and parameters: {'n_estimators': 514, 'max_depth': 12, 'learning_rate': 0.5300714512293007, 'gamma': 0.06686213254636227, 'min_child_weight': 2, 'subsample': 0.7598964166427791, 'colsample_bytree': 0.6527821461167355, 'reg_alpha': 0.0007257680068320631, 'reg_lambda': 2.053211374630651e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,301] Trial 53 finished with value: 0.9352690787473396 and parameters: {'n_estimators': 506, 'max_depth': 12, 'learning_rate': 0.571256600848416, 'gamma': 0.004555999545517148, 'min_child_weight': 9, 'subsample': 0.7047240133608822, 'colsample_bytree': 0.5018984188314298, 'reg_alpha': 0.0005907798905113109, 'reg_lambda': 2.4734342938311394e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,375] Trial 54 finished with value: 0.9644775514340731 and parameters: {'n_estimators': 395, 'max_depth': 13, 'learning_rate': 0.6124317734833269, 'gamma': 0.00048108720311051555, 'min_child_weight': 1, 'subsample': 0.7718507840031281, 'colsample_bytree': 0.6489094093412939, 'reg_alpha': 0.00010645026093228777, 'reg_lambda': 3.4160412117423306e-08}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,451] Trial 55 finished with value: 0.9688887199756765 and parameters: {'n_estimators': 463, 'max_depth': 18, 'learning_rate': 0.4202773904272926, 'gamma': 0.12392807749675176, 'min_child_weight': 2, 'subsample': 0.8134953557614573, 'colsample_bytree': 0.5607537502942631, 'reg_alpha': 0.00023820341543495421, 'reg_lambda': 2.1461245433286342e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,541] Trial 56 finished with value: 0.9663702239789196 and parameters: {'n_estimators': 669, 'max_depth': 10, 'learning_rate': 0.48574283632282905, 'gamma': 0.4148692898234699, 'min_child_weight': 1, 'subsample': 0.7307151250713312, 'colsample_bytree': 0.6678470212859086, 'reg_alpha': 0.008252969517073406, 'reg_lambda': 1.1251409603467727e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,616] Trial 57 finished with value: 0.9625139353400222 and parameters: {'n_estimators': 525, 'max_depth': 7, 'learning_rate': 0.5519120903294772, 'gamma': 0.0001874680975299932, 'min_child_weight': 5, 'subsample': 0.8900352044342466, 'colsample_bytree': 0.6932159225648519, 'reg_alpha': 0.002517108855212675, 'reg_lambda': 4.297366901491959e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,682] Trial 58 finished with value: 0.966405695753522 and parameters: {'n_estimators': 306, 'max_depth': 15, 'learning_rate': 0.3674085407668765, 'gamma': 0.0017976084371012489, 'min_child_weight': 2, 'subsample': 0.824737146000951, 'colsample_bytree': 0.7399794252049822, 'reg_alpha': 0.015847378796743628, 'reg_lambda': 0.0005358852795940928}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,783] Trial 59 finished with value: 0.9697856491334752 and parameters: {'n_estimators': 774, 'max_depth': 13, 'learning_rate': 0.6457443852498842, 'gamma': 0.012496329388736885, 'min_child_weight': 1, 'subsample': 0.793838230860561, 'colsample_bytree': 0.5836425111317189, 'reg_alpha': 2.1754437677486564e-05, 'reg_lambda': 0.03337705451236421}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,846] Trial 60 finished with value: 0.963887199756765 and parameters: {'n_estimators': 382, 'max_depth': 12, 'learning_rate': 0.47328611057555103, 'gamma': 0.0424604798937201, 'min_child_weight': 4, 'subsample': 0.934552791164968, 'colsample_bytree': 0.7790054412552747, 'reg_alpha': 0.0011101990270547515, 'reg_lambda': 1.6827865084742688e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,925] Trial 61 finished with value: 0.9660205736292694 and parameters: {'n_estimators': 545, 'max_depth': 11, 'learning_rate': 0.5055055462729076, 'gamma': 0.18056516452373952, 'min_child_weight': 3, 'subsample': 0.7519924075640182, 'colsample_bytree': 0.6178207309513841, 'reg_alpha': 0.0020172691789128233, 'reg_lambda': 3.9215049717299714e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,998] Trial 62 finished with value: 0.9557236242018851 and parameters: {'n_estimators': 473, 'max_depth': 11, 'learning_rate': 0.5400019943938102, 'gamma': 0.07754945232934854, 'min_child_weight': 2, 'subsample': 0.691256641899452, 'colsample_bytree': 0.6416326406060736, 'reg_alpha': 0.003532251580912962, 'reg_lambda': 1.0910716788302746e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,075] Trial 63 finished with value: 0.9659648322691801 and parameters: {'n_estimators': 640, 'max_depth': 10, 'learning_rate': 0.5246673195092458, 'gamma': 0.017184255393415157, 'min_child_weight': 1, 'subsample': 0.7639435627387441, 'colsample_bytree': 0.660278919577028, 'reg_alpha': 0.0005455413550718301, 'reg_lambda': 1.917088427074494e-08}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,139] Trial 64 finished with value: 0.964343265430222 and parameters: {'n_estimators': 442, 'max_depth': 14, 'learning_rate': 0.6003911375434905, 'gamma': 0.037188909985777056, 'min_child_weight': 3, 'subsample': 0.8347898516250483, 'colsample_bytree': 0.6269187811627178, 'reg_alpha': 0.0011552312420663807, 'reg_lambda': 2.833228903339653e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,180] Trial 65 finished with value: 0.9688912536738623 and parameters: {'n_estimators': 27, 'max_depth': 16, 'learning_rate': 0.2882497364553881, 'gamma': 0.0009365344901339396, 'min_child_weight': 2, 'subsample': 0.7470376879442628, 'colsample_bytree': 0.7041041755942481, 'reg_alpha': 0.08121948743500555, 'reg_lambda': 5.089309275914002e-08}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,281] Trial 66 finished with value: 0.9698261883044491 and parameters: {'n_estimators': 580, 'max_depth': 9, 'learning_rate': 0.4159616356940845, 'gamma': 0.5831219162124316, 'min_child_weight': 1, 'subsample': 0.982382322395441, 'colsample_bytree': 0.6102710521767731, 'reg_alpha': 0.0059321708676018815, 'reg_lambda': 0.005835785017549864}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,358] Trial 67 finished with value: 0.9618602412080672 and parameters: {'n_estimators': 534, 'max_depth': 8, 'learning_rate': 0.5710556707328297, 'gamma': 0.09669043321056411, 'min_child_weight': 3, 'subsample': 0.9073873458628307, 'colsample_bytree': 0.6799121381784294, 'reg_alpha': 0.0363553592541077, 'reg_lambda': 0.0010027836004984157}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,457] Trial 68 finished with value: 0.967196209587514 and parameters: {'n_estimators': 936, 'max_depth': 12, 'learning_rate': 0.49474283126858015, 'gamma': 0.0038977451885714052, 'min_child_weight': 2, 'subsample': 0.718024396773361, 'colsample_bytree': 0.5552789770779454, 'reg_alpha': 0.00037830643324867133, 'reg_lambda': 1.1088488335267902e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,510] Trial 69 finished with value: 0.955052194182629 and parameters: {'n_estimators': 113, 'max_depth': 14, 'learning_rate': 0.5265511334361885, 'gamma': 0.002516218958369442, 'min_child_weight': 1, 'subsample': 0.7984530114493523, 'colsample_bytree': 0.7246949533111133, 'reg_alpha': 0.009898780192040475, 'reg_lambda': 0.0002248622535206601}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,573] Trial 70 finished with value: 0.9673761021587108 and parameters: {'n_estimators': 361, 'max_depth': 11, 'learning_rate': 0.4500338383720486, 'gamma': 7.97419217113888e-05, 'min_child_weight': 1, 'subsample': 0.7758735699887569, 'colsample_bytree': 0.6353171405510678, 'reg_alpha': 0.003990138744326455, 'reg_lambda': 6.367408215373258e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,661] Trial 71 finished with value: 0.9699883449883451 and parameters: {'n_estimators': 574, 'max_depth': 9, 'learning_rate': 0.39331230829103997, 'gamma': 0.5832162124136367, 'min_child_weight': 1, 'subsample': 0.9892047975972974, 'colsample_bytree': 0.6070149608820187, 'reg_alpha': 0.005905898119536387, 'reg_lambda': 0.006704882688681093}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,747] Trial 72 finished with value: 0.9688507145028884 and parameters: {'n_estimators': 499, 'max_depth': 7, 'learning_rate': 0.38244445432292384, 'gamma': 0.18146664800759046, 'min_child_weight': 2, 'subsample': 0.9596340961165732, 'colsample_bytree': 0.572044864462482, 'reg_alpha': 0.016134020929382414, 'reg_lambda': 0.01234831939559891}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,846] Trial 73 finished with value: 0.9730591871896219 and parameters: {'n_estimators': 604, 'max_depth': 9, 'learning_rate': 0.3523875117331137, 'gamma': 0.5869038873091967, 'min_child_weight': 1, 'subsample': 0.9973259663877005, 'colsample_bytree': 0.6032453080408623, 'reg_alpha': 0.0022034163758147033, 'reg_lambda': 0.003049196789395216}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,943] Trial 74 finished with value: 0.9726867335562988 and parameters: {'n_estimators': 643, 'max_depth': 10, 'learning_rate': 0.3115429292430983, 'gamma': 0.036960550625807345, 'min_child_weight': 1, 'subsample': 0.9228507492640425, 'colsample_bytree': 0.5847404975899988, 'reg_alpha': 0.0014779764401295955, 'reg_lambda': 0.003412426872991884}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:46,042] Trial 75 finished with value: 0.9674419783115435 and parameters: {'n_estimators': 736, 'max_depth': 6, 'learning_rate': 0.31250026585052976, 'gamma': 0.00702536125685206, 'min_child_weight': 1, 'subsample': 0.9354922617992198, 'colsample_bytree': 0.5904428924919242, 'reg_alpha': 0.00019799922342255818, 'reg_lambda': 0.002649876404494166}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:46,140] Trial 76 finished with value: 0.96846305868045 and parameters: {'n_estimators': 662, 'max_depth': 10, 'learning_rate': 0.3376390484742646, 'gamma': 0.17746602873003298, 'min_child_weight': 1, 'subsample': 0.9210632567481764, 'colsample_bytree': 0.531169103386247, 'reg_alpha': 5.299213937151595e-05, 'reg_lambda': 0.0003542587698556304}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:46,242] Trial 77 finished with value: 0.9755472788081484 and parameters: {'n_estimators': 699, 'max_depth': 8, 'learning_rate': 0.3024552441518453, 'gamma': 0.031847215034954184, 'min_child_weight': 1, 'subsample': 0.9453725012935073, 'colsample_bytree': 0.5761387875938053, 'reg_alpha': 0.002617366611378274, 'reg_lambda': 0.0010349784161099026}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,342] Trial 78 finished with value: 0.9712754636667679 and parameters: {'n_estimators': 710, 'max_depth': 16, 'learning_rate': 0.2782864761065816, 'gamma': 0.025218929923798795, 'min_child_weight': 1, 'subsample': 0.9452026017018716, 'colsample_bytree': 0.5742454517084862, 'reg_alpha': 0.0007904896535609112, 'reg_lambda': 0.0010678161736113964}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,439] Trial 79 finished with value: 0.9720355731225296 and parameters: {'n_estimators': 705, 'max_depth': 8, 'learning_rate': 0.24162738268963288, 'gamma': 0.03242084611379141, 'min_child_weight': 1, 'subsample': 0.9990849392959138, 'colsample_bytree': 0.5707898574308613, 'reg_alpha': 0.0007599244448927335, 'reg_lambda': 0.000865693881036213}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,540] Trial 80 finished with value: 0.9663651565825478 and parameters: {'n_estimators': 715, 'max_depth': 8, 'learning_rate': 0.2321298214642324, 'gamma': 0.03022699849641668, 'min_child_weight': 1, 'subsample': 0.9755760553478194, 'colsample_bytree': 0.5183018267013588, 'reg_alpha': 7.536762919465367e-06, 'reg_lambda': 0.0008972684138130091}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,634] Trial 81 finished with value: 0.9711842505320767 and parameters: {'n_estimators': 611, 'max_depth': 6, 'learning_rate': 0.202585095609433, 'gamma': 0.015614516083160477, 'min_child_weight': 1, 'subsample': 0.9438468399025172, 'colsample_bytree': 0.5749914104204584, 'reg_alpha': 0.0007169577786597087, 'reg_lambda': 0.003665927983254753}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,722] Trial 82 finished with value: 0.9691876963616094 and parameters: {'n_estimators': 609, 'max_depth': 6, 'learning_rate': 0.1869983439603146, 'gamma': 0.017565215748102506, 'min_child_weight': 1, 'subsample': 0.9986384186074727, 'colsample_bytree': 0.5694324397593564, 'reg_alpha': 0.0018715550848706019, 'reg_lambda': 0.0038007089962539624}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,829] Trial 83 finished with value: 0.9702011756359583 and parameters: {'n_estimators': 690, 'max_depth': 5, 'learning_rate': 0.15378234192456952, 'gamma': 0.026585421213008446, 'min_child_weight': 1, 'subsample': 0.9471578642997183, 'colsample_bytree': 0.5770861818398159, 'reg_alpha': 0.00014343058886510785, 'reg_lambda': 0.0015367425711003662}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,921] Trial 84 finished with value: 0.9754687341643864 and parameters: {'n_estimators': 639, 'max_depth': 4, 'learning_rate': 0.2487735126244442, 'gamma': 0.013668381092022869, 'min_child_weight': 1, 'subsample': 0.9738876470197214, 'colsample_bytree': 0.5393776820447042, 'reg_alpha': 6.061029273544998e-05, 'reg_lambda': 0.0020237631280064475}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:47,010] Trial 85 finished with value: 0.9716479173000911 and parameters: {'n_estimators': 648, 'max_depth': 3, 'learning_rate': 0.25369031622209937, 'gamma': 0.011189099120964408, 'min_child_weight': 1, 'subsample': 0.9618607275528647, 'colsample_bytree': 0.5403278959911854, 'reg_alpha': 6.770838783028626e-05, 'reg_lambda': 0.004437258057055608}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:47,109] Trial 86 finished with value: 0.969990878686531 and parameters: {'n_estimators': 765, 'max_depth': 2, 'learning_rate': 0.24109962829948212, 'gamma': 0.010123695604080735, 'min_child_weight': 1, 'subsample': 0.9745058224401574, 'colsample_bytree': 0.5299920014608653, 'reg_alpha': 3.632267987330727e-05, 'reg_lambda': 0.009842578847590693}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:47,206] Trial 87 finished with value: 0.9775793047532177 and parameters: {'n_estimators': 636, 'max_depth': 3, 'learning_rate': 0.28911459468011935, 'gamma': 0.0026877179567177173, 'min_child_weight': 1, 'subsample': 0.9884898945689472, 'colsample_bytree': 0.5529899112143574, 'reg_alpha': 8.780578569353003e-06, 'reg_lambda': 0.024175358439225716}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,291] Trial 88 finished with value: 0.9618374379243946 and parameters: {'n_estimators': 630, 'max_depth': 3, 'learning_rate': 0.3030644325616155, 'gamma': 0.0014905115676082498, 'min_child_weight': 7, 'subsample': 0.9611256405654685, 'colsample_bytree': 0.5008769080768224, 'reg_alpha': 8.389249095912817e-07, 'reg_lambda': 0.025573250031303514}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,384] Trial 89 finished with value: 0.9702391811087464 and parameters: {'n_estimators': 648, 'max_depth': 2, 'learning_rate': 0.24974925657004052, 'gamma': 0.005400230740828263, 'min_child_weight': 2, 'subsample': 0.98727769647163, 'colsample_bytree': 0.542979554752891, 'reg_alpha': 6.773579449524946e-05, 'reg_lambda': 0.13938797071958295}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,484] Trial 90 finished with value: 0.9713134691395562 and parameters: {'n_estimators': 678, 'max_depth': 4, 'learning_rate': 0.27329622005890974, 'gamma': 0.0025640663065522483, 'min_child_weight': 1, 'subsample': 0.9685762941440739, 'colsample_bytree': 0.5533183680424663, 'reg_alpha': 9.554742944191967e-06, 'reg_lambda': 0.05646506170705333}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,600] Trial 91 finished with value: 0.9720735785953177 and parameters: {'n_estimators': 685, 'max_depth': 4, 'learning_rate': 0.27964910528085046, 'gamma': 0.002726438477417822, 'min_child_weight': 1, 'subsample': 0.9999643990452035, 'colsample_bytree': 0.5523292566223091, 'reg_alpha': 1.3960839467745119e-05, 'reg_lambda': 0.01415347048036145}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,692] Trial 92 finished with value: 0.9752204317421709 and parameters: {'n_estimators': 593, 'max_depth': 4, 'learning_rate': 0.32272873880627245, 'gamma': 0.0003076681496953475, 'min_child_weight': 1, 'subsample': 0.9988143324319202, 'colsample_bytree': 0.5182298233134042, 'reg_alpha': 4.764947763017983e-06, 'reg_lambda': 0.012883267517371262}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,777] Trial 93 finished with value: 0.9702746528833485 and parameters: {'n_estimators': 592, 'max_depth': 4, 'learning_rate': 0.32321683238270205, 'gamma': 0.00023242624645060717, 'min_child_weight': 1, 'subsample': 0.9883656895313044, 'colsample_bytree': 0.5249002470585026, 'reg_alpha': 3.177832241884098e-06, 'reg_lambda': 0.017907514716424745}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,866] Trial 94 finished with value: 0.9754687341643864 and parameters: {'n_estimators': 719, 'max_depth': 5, 'learning_rate': 0.35309665196705153, 'gamma': 0.0012381542386533933, 'min_child_weight': 2, 'subsample': 0.9938001959815986, 'colsample_bytree': 0.5135263406023138, 'reg_alpha': 2.140299584024884e-05, 'reg_lambda': 0.010354897273928652}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,964] Trial 95 finished with value: 0.9702619843924193 and parameters: {'n_estimators': 813, 'max_depth': 4, 'learning_rate': 0.35202078039521256, 'gamma': 0.0008558118176606106, 'min_child_weight': 2, 'subsample': 0.9786791914929385, 'colsample_bytree': 0.5169883732201127, 'reg_alpha': 4.819331670670429e-06, 'reg_lambda': 0.01225335075642242}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,050] Trial 96 finished with value: 0.9659420289855072 and parameters: {'n_estimators': 549, 'max_depth': 5, 'learning_rate': 0.30573045471770227, 'gamma': 0.0006382196831107483, 'min_child_weight': 2, 'subsample': 0.9975854577557746, 'colsample_bytree': 0.5149033410261374, 'reg_alpha': 1.7285610267319068e-05, 'reg_lambda': 0.04954756540940724}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,140] Trial 97 finished with value: 0.9701733049559136 and parameters: {'n_estimators': 726, 'max_depth': 2, 'learning_rate': 0.2877388004810307, 'gamma': 0.0003280781904783974, 'min_child_weight': 1, 'subsample': 0.9563657324404314, 'colsample_bytree': 0.5071027752196428, 'reg_alpha': 1.6962797991959727e-05, 'reg_lambda': 0.00907410879093517}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,228] Trial 98 finished with value: 0.9579279416235937 and parameters: {'n_estimators': 753, 'max_depth': 1, 'learning_rate': 0.34676644343134116, 'gamma': 0.0012565205080685606, 'min_child_weight': 2, 'subsample': 0.9724664289612212, 'colsample_bytree': 0.5608401123520345, 'reg_alpha': 1.398799276624877e-06, 'reg_lambda': 0.15340330599489194}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,317] Trial 99 finished with value: 0.9712729299685823 and parameters: {'n_estimators': 628, 'max_depth': 3, 'learning_rate': 0.3685623760852724, 'gamma': 0.00016314010705137475, 'min_child_weight': 1, 'subsample': 0.9018849176689584, 'colsample_bytree': 0.5526193503254366, 'reg_alpha': 3.4172598118958266e-06, 'reg_lambda': 0.35726720012149144}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,408] Trial 100 finished with value: 0.9684123847167324 and parameters: {'n_estimators': 685, 'max_depth': 5, 'learning_rate': 0.32205265663271354, 'gamma': 0.0003733394372953507, 'min_child_weight': 2, 'subsample': 0.9269329238786695, 'colsample_bytree': 0.5328390047076582, 'reg_alpha': 6.468453572696246e-06, 'reg_lambda': 0.0247247964033616}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,492] Trial 101 finished with value: 0.9734341745211312 and parameters: {'n_estimators': 657, 'max_depth': 4, 'learning_rate': 0.2902610534781817, 'gamma': 0.003144326892729591, 'min_child_weight': 1, 'subsample': 0.9994520720533928, 'colsample_bytree': 0.5979372134689044, 'reg_alpha': 2.811792565093441e-05, 'reg_lambda': 0.0024288390385784997}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,590] Trial 102 finished with value: 0.9678017634539373 and parameters: {'n_estimators': 794, 'max_depth': 4, 'learning_rate': 0.29965776922838716, 'gamma': 0.003105619445624373, 'min_child_weight': 1, 'subsample': 0.9811178081384474, 'colsample_bytree': 0.5970710263821791, 'reg_alpha': 3.448408606278336e-05, 'reg_lambda': 0.0025213111005363957}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,680] Trial 103 finished with value: 0.9684681260768218 and parameters: {'n_estimators': 663, 'max_depth': 4, 'learning_rate': 0.26839935650628705, 'gamma': 0.0005156188710353528, 'min_child_weight': 1, 'subsample': 0.9892553837421945, 'colsample_bytree': 0.5402218509766766, 'reg_alpha': 1.2238097567923076e-05, 'reg_lambda': 0.013305019890137302}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,768] Trial 104 finished with value: 0.9755194081281037 and parameters: {'n_estimators': 560, 'max_depth': 3, 'learning_rate': 0.28236255406126465, 'gamma': 0.004741677790575585, 'min_child_weight': 1, 'subsample': 0.9531167819448579, 'colsample_bytree': 0.5099770858154159, 'reg_alpha': 2.984910631985938e-05, 'reg_lambda': 0.007518398425430544}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,857] Trial 105 finished with value: 0.9730085132259045 and parameters: {'n_estimators': 596, 'max_depth': 2, 'learning_rate': 0.3222004116025429, 'gamma': 0.004489752812161376, 'min_child_weight': 1, 'subsample': 0.9352956487444385, 'colsample_bytree': 0.5865015029021471, 'reg_alpha': 2.7008940823248416e-05, 'reg_lambda': 0.007828445330780436}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,937] Trial 106 finished with value: 0.9669631093544137 and parameters: {'n_estimators': 595, 'max_depth': 2, 'learning_rate': 0.3267714012542968, 'gamma': 0.0016705946716529846, 'min_child_weight': 1, 'subsample': 0.9536853948914599, 'colsample_bytree': 0.5893227042142406, 'reg_alpha': 2.1190401208330304e-05, 'reg_lambda': 0.0063492970335785335}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,012] Trial 107 finished with value: 0.9649944258639911 and parameters: {'n_estimators': 551, 'max_depth': 1, 'learning_rate': 0.3576194826916017, 'gamma': 0.004801886110733527, 'min_child_weight': 6, 'subsample': 0.9338819770386118, 'colsample_bytree': 0.6214947240444341, 'reg_alpha': 2.8234266675465392e-05, 'reg_lambda': 0.008051822527829319}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,099] Trial 108 finished with value: 0.9720609101043882 and parameters: {'n_estimators': 595, 'max_depth': 3, 'learning_rate': 0.31458876017437437, 'gamma': 0.008358899230048938, 'min_child_weight': 1, 'subsample': 0.968750010105244, 'colsample_bytree': 0.6043042278252939, 'reg_alpha': 2.393229312399412e-06, 'reg_lambda': 0.0021086902788013838}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,176] Trial 109 finished with value: 0.9595520421607379 and parameters: {'n_estimators': 564, 'max_depth': 3, 'learning_rate': 0.29332591763899823, 'gamma': 0.002008519656446403, 'min_child_weight': 10, 'subsample': 0.9178749512403971, 'colsample_bytree': 0.5624548512353742, 'reg_alpha': 6.279674953618662e-05, 'reg_lambda': 0.03769905974473238}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,256] Trial 110 finished with value: 0.9681640822945171 and parameters: {'n_estimators': 627, 'max_depth': 2, 'learning_rate': 0.21619927350223261, 'gamma': 0.0009373960888666258, 'min_child_weight': 2, 'subsample': 0.6307794924226682, 'colsample_bytree': 0.5836006154710169, 'reg_alpha': 2.713808381396758e-07, 'reg_lambda': 0.0050776218812680785}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,342] Trial 111 finished with value: 0.9708346001824262 and parameters: {'n_estimators': 651, 'max_depth': 5, 'learning_rate': 0.40366773427286373, 'gamma': 0.005707361249345923, 'min_child_weight': 1, 'subsample': 0.9799469111616341, 'colsample_bytree': 0.5116600324384395, 'reg_alpha': 8.85253713948703e-06, 'reg_lambda': 0.003065231130945774}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,432] Trial 112 finished with value: 0.9736951454342758 and parameters: {'n_estimators': 583, 'max_depth': 3, 'learning_rate': 0.37574148917155586, 'gamma': 0.0009319568992135199, 'min_child_weight': 1, 'subsample': 0.9397410388904857, 'colsample_bytree': 0.5235594910355523, 'reg_alpha': 4.017162866775182e-05, 'reg_lambda': 0.018251272759087948}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,520] Trial 113 finished with value: 0.973771156379852 and parameters: {'n_estimators': 578, 'max_depth': 3, 'learning_rate': 0.380812899535783, 'gamma': 0.0011512223457226971, 'min_child_weight': 1, 'subsample': 0.9388546288873797, 'colsample_bytree': 0.5352536425774438, 'reg_alpha': 9.09130166376462e-05, 'reg_lambda': 0.018725988923139904}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,598] Trial 114 finished with value: 0.9737838248707813 and parameters: {'n_estimators': 530, 'max_depth': 3, 'learning_rate': 0.3742761757944042, 'gamma': 0.0029273154938769808, 'min_child_weight': 1, 'subsample': 0.9529626320951139, 'colsample_bytree': 0.5232564805201162, 'reg_alpha': 9.104169023548576e-05, 'reg_lambda': 0.01996768613708404}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,681] Trial 115 finished with value: 0.9756460930373974 and parameters: {'n_estimators': 533, 'max_depth': 3, 'learning_rate': 0.3787657790858809, 'gamma': 0.0011307839139740017, 'min_child_weight': 1, 'subsample': 0.9535686443026108, 'colsample_bytree': 0.5245456491257551, 'reg_alpha': 0.00013522790859490737, 'reg_lambda': 0.019711799698721878}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,755] Trial 116 finished with value: 0.9635198135198134 and parameters: {'n_estimators': 485, 'max_depth': 3, 'learning_rate': 0.38091477840580124, 'gamma': 0.0009720468741725009, 'min_child_weight': 2, 'subsample': 0.8986807103789741, 'colsample_bytree': 0.5273155593064995, 'reg_alpha': 0.00013848719337144623, 'reg_lambda': 0.08091061668198583}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,834] Trial 117 finished with value: 0.9717289956420393 and parameters: {'n_estimators': 527, 'max_depth': 4, 'learning_rate': 0.4076052802456525, 'gamma': 0.0004831402272338826, 'min_child_weight': 1, 'subsample': 0.9533851366158632, 'colsample_bytree': 0.5220037354837226, 'reg_alpha': 4.5139430500113255e-05, 'reg_lambda': 0.02575574317660115}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,924] Trial 118 finished with value: 0.9752331002331003 and parameters: {'n_estimators': 563, 'max_depth': 3, 'learning_rate': 0.369521549644023, 'gamma': 0.0033558215982748703, 'min_child_weight': 1, 'subsample': 0.9667985061852574, 'colsample_bytree': 0.5372400830436947, 'reg_alpha': 9.504911886451962e-05, 'reg_lambda': 0.018904666487589226}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,013] Trial 119 finished with value: 0.9705736292692814 and parameters: {'n_estimators': 563, 'max_depth': 4, 'learning_rate': 0.4299915817303335, 'gamma': 0.001525288316607799, 'min_child_weight': 1, 'subsample': 0.9689561356982478, 'colsample_bytree': 0.5359613906712454, 'reg_alpha': 8.351303475967823e-05, 'reg_lambda': 0.018419935953742344}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,090] Trial 120 finished with value: 0.9639074693422518 and parameters: {'n_estimators': 451, 'max_depth': 3, 'learning_rate': 0.3667210874551086, 'gamma': 0.0021214031984273544, 'min_child_weight': 2, 'subsample': 0.9432651878904321, 'colsample_bytree': 0.5014124944408871, 'reg_alpha': 0.0003167811707490163, 'reg_lambda': 0.04607793156075455}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,171] Trial 121 finished with value: 0.9724004256612953 and parameters: {'n_estimators': 580, 'max_depth': 3, 'learning_rate': 0.38856872366310524, 'gamma': 0.0007746428169296834, 'min_child_weight': 1, 'subsample': 0.9623910956260555, 'colsample_bytree': 0.5119448445892998, 'reg_alpha': 0.0001022046692298684, 'reg_lambda': 0.01876632074345833}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,249] Trial 122 finished with value: 0.9663018141279013 and parameters: {'n_estimators': 523, 'max_depth': 5, 'learning_rate': 0.34228646898366927, 'gamma': 0.004028194445590085, 'min_child_weight': 1, 'subsample': 0.9828478575776481, 'colsample_bytree': 0.5450122834491693, 'reg_alpha': 4.336905329638909e-05, 'reg_lambda': 0.07311566300587641}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,326] Trial 123 finished with value: 0.9660028377419682 and parameters: {'n_estimators': 543, 'max_depth': 2, 'learning_rate': 0.3710652116662308, 'gamma': 0.003426110492596931, 'min_child_weight': 1, 'subsample': 0.9519074894178458, 'colsample_bytree': 0.52062981297652, 'reg_alpha': 0.00019606561378930507, 'reg_lambda': 0.00010956050738603163}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,402] Trial 124 finished with value: 0.9675078544643763 and parameters: {'n_estimators': 490, 'max_depth': 3, 'learning_rate': 0.3419021639421203, 'gamma': 0.001379753702423482, 'min_child_weight': 1, 'subsample': 0.5402074886692497, 'colsample_bytree': 0.534963564474138, 'reg_alpha': 2.4804707361280354e-05, 'reg_lambda': 0.02366181477486779}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,492] Trial 125 finished with value: 0.9664031620553359 and parameters: {'n_estimators': 623, 'max_depth': 4, 'learning_rate': 0.2584426107557688, 'gamma': 0.0002969583549970284, 'min_child_weight': 1, 'subsample': 0.8659075091283825, 'colsample_bytree': 0.5477391905798454, 'reg_alpha': 6.0849397689869715e-06, 'reg_lambda': 0.03055499300789043}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,569] Trial 126 finished with value: 0.9709739535826492 and parameters: {'n_estimators': 564, 'max_depth': 3, 'learning_rate': 0.3607708090917786, 'gamma': 0.007904872146312887, 'min_child_weight': 1, 'subsample': 0.9732660624180509, 'colsample_bytree': 0.5596402152998722, 'reg_alpha': 0.0001532572414280914, 'reg_lambda': 0.1245305580605709}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,660] Trial 127 finished with value: 0.9620680044593088 and parameters: {'n_estimators': 507, 'max_depth': 6, 'learning_rate': 0.40969970909179665, 'gamma': 0.002569636211762046, 'min_child_weight': 2, 'subsample': 0.8829928862860841, 'colsample_bytree': 0.5098754820895927, 'reg_alpha': 1.3035647256514827e-05, 'reg_lambda': 0.010289122123771933}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,736] Trial 128 finished with value: 0.9603476233911017 and parameters: {'n_estimators': 577, 'max_depth': 1, 'learning_rate': 0.39060663548307156, 'gamma': 0.0010891361828261408, 'min_child_weight': 1, 'subsample': 0.9379188131627437, 'colsample_bytree': 0.524948913298735, 'reg_alpha': 8.586777823699555e-05, 'reg_lambda': 0.04302715195504146}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,817] Trial 129 finished with value: 0.9663702239789196 and parameters: {'n_estimators': 546, 'max_depth': 2, 'learning_rate': 0.3340394526859328, 'gamma': 0.005928493392740887, 'min_child_weight': 1, 'subsample': 0.9854164381951216, 'colsample_bytree': 0.5401827154061658, 'reg_alpha': 3.574390952002835e-05, 'reg_lambda': 0.01684875458666302}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,905] Trial 130 finished with value: 0.9653162055335969 and parameters: {'n_estimators': 616, 'max_depth': 4, 'learning_rate': 0.28549506379050643, 'gamma': 1.2263018757725954e-07, 'min_child_weight': 2, 'subsample': 0.959035504220871, 'colsample_bytree': 0.5004808635645343, 'reg_alpha': 6.108068069373782e-05, 'reg_lambda': 4.081789431923016e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,995] Trial 131 finished with value: 0.974407114624506 and parameters: {'n_estimators': 607, 'max_depth': 5, 'learning_rate': 0.355606899809378, 'gamma': 0.0016875775407594427, 'min_child_weight': 1, 'subsample': 0.9899274318285423, 'colsample_bytree': 0.522467631554332, 'reg_alpha': 1.9439920919411324e-05, 'reg_lambda': 0.005478042686972311}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,083] Trial 132 finished with value: 0.9697349751697578 and parameters: {'n_estimators': 659, 'max_depth': 5, 'learning_rate': 0.3758099733710491, 'gamma': 0.0020911550697864313, 'min_child_weight': 1, 'subsample': 0.9896734709877024, 'colsample_bytree': 0.5200962421716877, 'reg_alpha': 1.0531070308464693e-05, 'reg_lambda': 0.006260553029093111}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,160] Trial 133 finished with value: 0.9691623593797507 and parameters: {'n_estimators': 579, 'max_depth': 4, 'learning_rate': 0.3543435466787781, 'gamma': 0.003457287339258925, 'min_child_weight': 1, 'subsample': 0.9699357364188769, 'colsample_bytree': 0.5319377512135547, 'reg_alpha': 1.6344689723836534e-05, 'reg_lambda': 0.011513426714595142}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,249] Trial 134 finished with value: 0.9685137326441675 and parameters: {'n_estimators': 609, 'max_depth': 3, 'learning_rate': 0.29969094509558114, 'gamma': 0.0006201750540023973, 'min_child_weight': 1, 'subsample': 0.9465508766827356, 'colsample_bytree': 0.549628779727799, 'reg_alpha': 0.00023383467565098683, 'reg_lambda': 0.00473897887352641}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,340] Trial 135 finished with value: 0.9702113104287017 and parameters: {'n_estimators': 702, 'max_depth': 5, 'learning_rate': 0.39838626436610647, 'gamma': 0.013457480792657921, 'min_child_weight': 1, 'subsample': 0.9284918315242744, 'colsample_bytree': 0.5111760740688991, 'reg_alpha': 2.112013867824408e-05, 'reg_lambda': 0.0016412145138216558}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,416] Trial 136 finished with value: 0.9590706395054222 and parameters: {'n_estimators': 423, 'max_depth': 3, 'learning_rate': 0.42953000397831703, 'gamma': 0.0017375341373862645, 'min_child_weight': 9, 'subsample': 0.9781959850635785, 'colsample_bytree': 0.8378674178811536, 'reg_alpha': 9.858181986503538e-05, 'reg_lambda': 0.0322880013964512}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,504] Trial 137 finished with value: 0.973811695550826 and parameters: {'n_estimators': 728, 'max_depth': 4, 'learning_rate': 0.3342825551208779, 'gamma': 0.0013440099679389622, 'min_child_weight': 1, 'subsample': 0.9916941709687607, 'colsample_bytree': 0.5655061047088268, 'reg_alpha': 5.070174259490981e-05, 'reg_lambda': 0.05985267611255229}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,604] Trial 138 finished with value: 0.9692383703253269 and parameters: {'n_estimators': 749, 'max_depth': 4, 'learning_rate': 0.32844184046054403, 'gamma': 0.0010007539710985736, 'min_child_weight': 5, 'subsample': 0.9920762896755643, 'colsample_bytree': 0.565157003127687, 'reg_alpha': 4.908631252458206e-05, 'reg_lambda': 0.0959049021065359}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,694] Trial 139 finished with value: 0.9708852741461437 and parameters: {'n_estimators': 673, 'max_depth': 5, 'learning_rate': 0.3774025399941191, 'gamma': 0.000643044874536142, 'min_child_weight': 1, 'subsample': 0.9651415410028824, 'colsample_bytree': 0.5256854732827111, 'reg_alpha': 4.714024807154563e-06, 'reg_lambda': 0.9912937619442326}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,783] Trial 140 finished with value: 0.9634792743488395 and parameters: {'n_estimators': 717, 'max_depth': 2, 'learning_rate': 0.3137203687154433, 'gamma': 0.0003873298406166423, 'min_child_weight': 1, 'subsample': 0.9913943483341556, 'colsample_bytree': 0.5377420413971642, 'reg_alpha': 3.32220834872906e-05, 'reg_lambda': 0.056686545270045595}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,872] Trial 141 finished with value: 0.9681032735380561 and parameters: {'n_estimators': 732, 'max_depth': 4, 'learning_rate': 0.3457977422562131, 'gamma': 0.002976971721662494, 'min_child_weight': 1, 'subsample': 0.9763124432392175, 'colsample_bytree': 0.5543880729679166, 'reg_alpha': 7.545227219322496e-05, 'reg_lambda': 0.009449314626667723}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,962] Trial 142 finished with value: 0.9723598864903213 and parameters: {'n_estimators': 632, 'max_depth': 3, 'learning_rate': 0.275963901659525, 'gamma': 0.0016243745622636782, 'min_child_weight': 1, 'subsample': 0.9530092292388275, 'colsample_bytree': 0.5175852195916012, 'reg_alpha': 0.0001427649603465201, 'reg_lambda': 0.0005683368270736766}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,051] Trial 143 finished with value: 0.9677688253775212 and parameters: {'n_estimators': 592, 'max_depth': 6, 'learning_rate': 0.3336579888058368, 'gamma': 0.00014631390669258675, 'min_child_weight': 1, 'subsample': 0.9999417063182031, 'colsample_bytree': 0.9335216594524222, 'reg_alpha': 4.6191952330179104e-05, 'reg_lambda': 0.016752760821593927}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,141] Trial 144 finished with value: 0.9641684402553968 and parameters: {'n_estimators': 529, 'max_depth': 4, 'learning_rate': 0.36114155417739013, 'gamma': 0.0013312075417919174, 'min_child_weight': 1, 'subsample': 0.9623533998092761, 'colsample_bytree': 0.5302807739145121, 'reg_alpha': 1.9198762008560404e-06, 'reg_lambda': 0.02423055657998778}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,232] Trial 145 finished with value: 0.9663144826188306 and parameters: {'n_estimators': 696, 'max_depth': 3, 'learning_rate': 0.29694209248501263, 'gamma': 0.006637136428949488, 'min_child_weight': 2, 'subsample': 0.9832551742092744, 'colsample_bytree': 0.5451968446750411, 'reg_alpha': 2.3355865575390215e-05, 'reg_lambda': 6.480226641591573e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,323] Trial 146 finished with value: 0.9722458700719571 and parameters: {'n_estimators': 772, 'max_depth': 2, 'learning_rate': 0.3119949296748683, 'gamma': 0.004385003172565624, 'min_child_weight': 1, 'subsample': 0.911161698166705, 'colsample_bytree': 0.5674565521458058, 'reg_alpha': 8.339882112703323e-06, 'reg_lambda': 0.22744493185559642}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,414] Trial 147 finished with value: 0.9705989662511403 and parameters: {'n_estimators': 649, 'max_depth': 5, 'learning_rate': 0.3886513667571667, 'gamma': 0.0023992741913581236, 'min_child_weight': 1, 'subsample': 0.9412909731446526, 'colsample_bytree': 0.5082665367483681, 'reg_alpha': 1.3917011685173996e-05, 'reg_lambda': 0.004983404179282378}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,505] Trial 148 finished with value: 0.9641785750481404 and parameters: {'n_estimators': 559, 'max_depth': 7, 'learning_rate': 0.2656435390958021, 'gamma': 0.010482805664855063, 'min_child_weight': 1, 'subsample': 0.9700690013382033, 'colsample_bytree': 0.553896550744323, 'reg_alpha': 2.703827604890988e-05, 'reg_lambda': 0.008979484259118622}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,595] Trial 149 finished with value: 0.9656785243741766 and parameters: {'n_estimators': 675, 'max_depth': 4, 'learning_rate': 0.3481169895361487, 'gamma': 0.0190297439645008, 'min_child_weight': 1, 'subsample': 0.9886286410235502, 'colsample_bytree': 0.5248371166735615, 'reg_alpha': 0.00011080258805194705, 'reg_lambda': 0.013823520690237876}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,686] Trial 150 finished with value: 0.971652984696463 and parameters: {'n_estimators': 610, 'max_depth': 3, 'learning_rate': 0.3647380803471352, 'gamma': 0.0007750215340674814, 'min_child_weight': 2, 'subsample': 0.9544048764946547, 'colsample_bytree': 0.578212060417031, 'reg_alpha': 0.0003801255473377791, 'reg_lambda': 0.03725850213457456}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,776] Trial 151 finished with value: 0.9720229046316003 and parameters: {'n_estimators': 592, 'max_depth': 9, 'learning_rate': 0.3464425517062153, 'gamma': 0.0012319969445261018, 'min_child_weight': 1, 'subsample': 0.9985073180656334, 'colsample_bytree': 0.5974960617683841, 'reg_alpha': 5.515700111193299e-05, 'reg_lambda': 0.0033159882823894545}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,865] Trial 152 finished with value: 0.9688507145028884 and parameters: {'n_estimators': 540, 'max_depth': 4, 'learning_rate': 0.38017768085764003, 'gamma': 0.002973199513913439, 'min_child_weight': 1, 'subsample': 0.9799912178341434, 'colsample_bytree': 0.5404784885391826, 'reg_alpha': 3.899089387434627e-05, 'reg_lambda': 0.0015310715824011964}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,954] Trial 153 finished with value: 0.9699376710246275 and parameters: {'n_estimators': 638, 'max_depth': 3, 'learning_rate': 0.3293247587583182, 'gamma': 1.080918771118752e-08, 'min_child_weight': 1, 'subsample': 0.9748569594260413, 'colsample_bytree': 0.5627494059605304, 'reg_alpha': 0.0001868642563379178, 'reg_lambda': 0.00610063335717874}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,045] Trial 154 finished with value: 0.9727247390290866 and parameters: {'n_estimators': 579, 'max_depth': 8, 'learning_rate': 0.3590865853470216, 'gamma': 0.00023242766577177755, 'min_child_weight': 1, 'subsample': 0.9961763419959316, 'colsample_bytree': 0.5001855233864979, 'reg_alpha': 4.938473306881137e-06, 'reg_lambda': 0.05945419728506628}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,132] Trial 155 finished with value: 0.9698236546062633 and parameters: {'n_estimators': 511, 'max_depth': 2, 'learning_rate': 0.23177088731265877, 'gamma': 0.00220051619789768, 'min_child_weight': 1, 'subsample': 0.9617219946146195, 'colsample_bytree': 0.5155296562213243, 'reg_alpha': 0.41356358892481515, 'reg_lambda': 0.0021647051888757846}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,221] Trial 156 finished with value: 0.9642849903719469 and parameters: {'n_estimators': 608, 'max_depth': 4, 'learning_rate': 0.310179089365562, 'gamma': 0.0004899069210826855, 'min_child_weight': 1, 'subsample': 0.989151895567528, 'colsample_bytree': 0.6155162461276559, 'reg_alpha': 7.038828394482472e-05, 'reg_lambda': 0.018486913379264905}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,306] Trial 157 finished with value: 0.968800040539171 and parameters: {'n_estimators': 625, 'max_depth': 3, 'learning_rate': 0.28337124920511253, 'gamma': 0.005312986290264966, 'min_child_weight': 1, 'subsample': 0.9471200013006852, 'colsample_bytree': 0.5371368095603188, 'reg_alpha': 2.126502030369528e-05, 'reg_lambda': 0.007672507188909957}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,396] Trial 158 finished with value: 0.9688127090301004 and parameters: {'n_estimators': 560, 'max_depth': 5, 'learning_rate': 0.24864922427836095, 'gamma': 0.001724231530528261, 'min_child_weight': 1, 'subsample': 0.9275859919551936, 'colsample_bytree': 0.5485555398820796, 'reg_alpha': 0.22167735775120456, 'reg_lambda': 0.012725979226750948}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,472] Trial 159 finished with value: 0.9690990169251039 and parameters: {'n_estimators': 466, 'max_depth': 7, 'learning_rate': 0.4138830978222457, 'gamma': 0.008325545281432306, 'min_child_weight': 2, 'subsample': 0.9825726014682536, 'colsample_bytree': 0.5288970024992221, 'reg_alpha': 1.1950616323811105e-05, 'reg_lambda': 0.004148040954584921}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,575] Trial 160 finished with value: 0.9681007398398702 and parameters: {'n_estimators': 665, 'max_depth': 2, 'learning_rate': 0.10656692051303243, 'gamma': 0.0034721265000381826, 'min_child_weight': 1, 'subsample': 0.6041603502459372, 'colsample_bytree': 0.8973681381628347, 'reg_alpha': 8.155092256320305e-07, 'reg_lambda': 0.0026912192428167675}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,653] Trial 161 finished with value: 0.9741334752204317 and parameters: {'n_estimators': 593, 'max_depth': 2, 'learning_rate': 0.3316977172429725, 'gamma': 0.00442101924584059, 'min_child_weight': 1, 'subsample': 0.9383014449372667, 'colsample_bytree': 0.583117916065411, 'reg_alpha': 3.380931076086002e-05, 'reg_lambda': 0.008524632802382586}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,731] Trial 162 finished with value: 0.9709106111280026 and parameters: {'n_estimators': 592, 'max_depth': 3, 'learning_rate': 0.3361791828373549, 'gamma': 0.000985104918156739, 'min_child_weight': 1, 'subsample': 0.9689753750776854, 'colsample_bytree': 0.582026572904053, 'reg_alpha': 2.9623097239471037e-05, 'reg_lambda': 0.023865897227663392}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,818] Trial 163 finished with value: 0.972364953886693 and parameters: {'n_estimators': 544, 'max_depth': 2, 'learning_rate': 0.36753628914761743, 'gamma': 0.003867620019904887, 'min_child_weight': 1, 'subsample': 0.9163941822885812, 'colsample_bytree': 0.5934172796052541, 'reg_alpha': 1.6872233434997325e-05, 'reg_lambda': 0.0012256804410906703}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,909] Trial 164 finished with value: 0.9649538866930174 and parameters: {'n_estimators': 644, 'max_depth': 4, 'learning_rate': 0.3217185820552294, 'gamma': 0.9074683779076849, 'min_child_weight': 1, 'subsample': 0.9404194835151828, 'colsample_bytree': 0.5716382974503587, 'reg_alpha': 4.5156868287806393e-05, 'reg_lambda': 0.009577284570238343}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,989] Trial 165 finished with value: 0.9582623897841289 and parameters: {'n_estimators': 572, 'max_depth': 1, 'learning_rate': 0.35434018519246835, 'gamma': 0.006054890244988751, 'min_child_weight': 1, 'subsample': 0.9565629468808314, 'colsample_bytree': 0.6064348733438767, 'reg_alpha': 0.00011506343284625452, 'reg_lambda': 0.03650487541601268}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,068] Trial 166 finished with value: 0.9660433769129421 and parameters: {'n_estimators': 606, 'max_depth': 3, 'learning_rate': 0.2967811217926221, 'gamma': 0.002177647575750638, 'min_child_weight': 4, 'subsample': 0.998649545486057, 'colsample_bytree': 0.5185902261954761, 'reg_alpha': 8.042129768295383e-05, 'reg_lambda': 0.014443731544619897}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,147] Trial 167 finished with value: 0.9681007398398702 and parameters: {'n_estimators': 690, 'max_depth': 4, 'learning_rate': 0.38997942152940307, 'gamma': 0.0013930912234913896, 'min_child_weight': 1, 'subsample': 0.977585735981025, 'colsample_bytree': 0.5600326728904678, 'reg_alpha': 8.024671426853231e-06, 'reg_lambda': 0.005881071752141783}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,225] Trial 168 finished with value: 0.9663524880916186 and parameters: {'n_estimators': 518, 'max_depth': 9, 'learning_rate': 0.37517946961696524, 'gamma': 0.2884197766559136, 'min_child_weight': 2, 'subsample': 0.9320238547852112, 'colsample_bytree': 0.5116644916138443, 'reg_alpha': 3.510454301920386e-05, 'reg_lambda': 0.00396091516537362}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,303] Trial 169 finished with value: 0.9733835005574136 and parameters: {'n_estimators': 493, 'max_depth': 3, 'learning_rate': 0.323016657794504, 'gamma': 0.0008040858558472051, 'min_child_weight': 1, 'subsample': 0.9650583288653142, 'colsample_bytree': 0.5335385167426343, 'reg_alpha': 0.00025883717994882905, 'reg_lambda': 1.4790057261225227e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,397] Trial 170 finished with value: 0.9701986419377724 and parameters: {'n_estimators': 490, 'max_depth': 3, 'learning_rate': 0.321492205338363, 'gamma': 0.0007229956299063446, 'min_child_weight': 1, 'subsample': 0.9471452120455542, 'colsample_bytree': 0.5341908031859132, 'reg_alpha': 5.7889158157425586e-05, 'reg_lambda': 2.5464473413471723e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,464] Trial 171 finished with value: 0.9694106618019662 and parameters: {'n_estimators': 215, 'max_depth': 2, 'learning_rate': 0.3439161658472922, 'gamma': 0.0011441221668909544, 'min_child_weight': 1, 'subsample': 0.9634326817470634, 'colsample_bytree': 0.5247209277418037, 'reg_alpha': 0.00016940381362453118, 'reg_lambda': 0.02385174376916467}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,555] Trial 172 finished with value: 0.9706167021384413 and parameters: {'n_estimators': 619, 'max_depth': 3, 'learning_rate': 0.3054421107140958, 'gamma': 0.0026032231277366247, 'min_child_weight': 1, 'subsample': 0.9860629143288514, 'colsample_bytree': 0.547967448961253, 'reg_alpha': 0.0002849202968485869, 'reg_lambda': 2.6299709321578504e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,645] Trial 173 finished with value: 0.971946893686024 and parameters: {'n_estimators': 720, 'max_depth': 4, 'learning_rate': 0.33341255577347795, 'gamma': 0.0016105012826958308, 'min_child_weight': 1, 'subsample': 0.9679139315267277, 'colsample_bytree': 0.5386463925647356, 'reg_alpha': 8.43176289243587e-05, 'reg_lambda': 4.340287507851219e-06}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,724] Trial 174 finished with value: 0.9716605857910207 and parameters: {'n_estimators': 557, 'max_depth': 5, 'learning_rate': 0.2901160057271195, 'gamma': 0.00032942746566321543, 'min_child_weight': 1, 'subsample': 0.9765070332415594, 'colsample_bytree': 0.5071537214617675, 'reg_alpha': 0.0004723169262131176, 'reg_lambda': 6.832514561560678e-06}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,805] Trial 175 finished with value: 0.9691116854160333 and parameters: {'n_estimators': 588, 'max_depth': 3, 'learning_rate': 0.3522900041666762, 'gamma': 0.004165093913741628, 'min_child_weight': 1, 'subsample': 0.9999358736000473, 'colsample_bytree': 0.5570975897786812, 'reg_alpha': 0.00011310018708618362, 'reg_lambda': 1.5899845363994675e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,907] Trial 176 finished with value: 0.9701859734468432 and parameters: {'n_estimators': 795, 'max_depth': 3, 'learning_rate': 0.2661263579232849, 'gamma': 0.0005314614635974421, 'min_child_weight': 1, 'subsample': 0.955262002780409, 'colsample_bytree': 0.5218601743864764, 'reg_alpha': 3.278095954186388e-05, 'reg_lambda': 0.007563842393120928}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,987] Trial 177 finished with value: 0.9691876963616094 and parameters: {'n_estimators': 528, 'max_depth': 4, 'learning_rate': 0.4052836482941531, 'gamma': 0.0007836995912045476, 'min_child_weight': 1, 'subsample': 0.9835358139883751, 'colsample_bytree': 0.5748069554328435, 'reg_alpha': 1.8927713418645845e-05, 'reg_lambda': 0.016993878052280156}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,078] Trial 178 finished with value: 0.9646042363433669 and parameters: {'n_estimators': 659, 'max_depth': 10, 'learning_rate': 0.3716414273907836, 'gamma': 0.0030133506411139394, 'min_child_weight': 2, 'subsample': 0.9398036029857711, 'colsample_bytree': 0.53143727573368, 'reg_alpha': 0.00023311010825420792, 'reg_lambda': 0.012640641270748694}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,167] Trial 179 finished with value: 0.9698616600790514 and parameters: {'n_estimators': 747, 'max_depth': 2, 'learning_rate': 0.32001440829474825, 'gamma': 0.0019126003149610587, 'min_child_weight': 1, 'subsample': 0.9707912347002509, 'colsample_bytree': 0.5423708785702983, 'reg_alpha': 5.966945807712596e-05, 'reg_lambda': 1.0493234578616303e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,248] Trial 180 finished with value: 0.9551535421100639 and parameters: {'n_estimators': 294, 'max_depth': 1, 'learning_rate': 0.3357416315742316, 'gamma': 0.007657877580656061, 'min_child_weight': 1, 'subsample': 0.9919818138814995, 'colsample_bytree': 0.5887452792406924, 'reg_alpha': 4.579238829952115e-05, 'reg_lambda': 0.0018385729955730126}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,341] Trial 181 finished with value: 0.9701226309921962 and parameters: {'n_estimators': 595, 'max_depth': 2, 'learning_rate': 0.3196711674185751, 'gamma': 0.004045724729064204, 'min_child_weight': 1, 'subsample': 0.9331559720774428, 'colsample_bytree': 0.5844164508168194, 'reg_alpha': 2.742025068307707e-05, 'reg_lambda': 0.009885387517462787}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,443] Trial 182 finished with value: 0.9688253775210296 and parameters: {'n_estimators': 571, 'max_depth': 2, 'learning_rate': 0.30577243814461674, 'gamma': 0.012880627685399902, 'min_child_weight': 1, 'subsample': 0.9485931009156126, 'colsample_bytree': 0.5996568259313692, 'reg_alpha': 1.3396606182173234e-05, 'reg_lambda': 0.007635969022558665}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,535] Trial 183 finished with value: 0.9674166413296849 and parameters: {'n_estimators': 629, 'max_depth': 3, 'learning_rate': 0.28188713644457714, 'gamma': 0.005235909540075137, 'min_child_weight': 1, 'subsample': 0.961053367499909, 'colsample_bytree': 0.6198251105511885, 'reg_alpha': 2.5215043925068256e-05, 'reg_lambda': 0.002628148822304905}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,589] Trial 184 finished with value: 0.9649437519002737 and parameters: {'n_estimators': 67, 'max_depth': 3, 'learning_rate': 0.35529559929163035, 'gamma': 0.001225158706094834, 'min_child_weight': 1, 'subsample': 0.9338994225805587, 'colsample_bytree': 0.5674075089505664, 'reg_alpha': 0.08714908351909771, 'reg_lambda': 0.004961439672981354}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,681] Trial 185 finished with value: 0.965017229147664 and parameters: {'n_estimators': 607, 'max_depth': 2, 'learning_rate': 0.3839038757913715, 'gamma': 0.002331336980927999, 'min_child_weight': 1, 'subsample': 0.9892104914873026, 'colsample_bytree': 0.5192707137105969, 'reg_alpha': 7.812769802730331e-05, 'reg_lambda': 0.033524561228580545}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,774] Trial 186 finished with value: 0.9667148069321984 and parameters: {'n_estimators': 835, 'max_depth': 6, 'learning_rate': 0.3428772238998707, 'gamma': 0.004906203351066525, 'min_child_weight': 1, 'subsample': 0.9769488668693691, 'colsample_bytree': 0.5510092209217737, 'reg_alpha': 0.00013871818028374805, 'reg_lambda': 0.01985471270961442}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,841] Trial 187 finished with value: 0.9673913043478259 and parameters: {'n_estimators': 253, 'max_depth': 4, 'learning_rate': 0.32508797810579004, 'gamma': 0.0009561938888235766, 'min_child_weight': 1, 'subsample': 0.9161395624008124, 'colsample_bytree': 0.9607189113456386, 'reg_alpha': 9.607969314415795e-06, 'reg_lambda': 1.3099693721755294e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,920] Trial 188 finished with value: 0.9691547582851932 and parameters: {'n_estimators': 546, 'max_depth': 5, 'learning_rate': 0.295502717565899, 'gamma': 0.009464505555965745, 'min_child_weight': 1, 'subsample': 0.9248654467114628, 'colsample_bytree': 0.5093090629574039, 'reg_alpha': 3.311414049778045e-05, 'reg_lambda': 0.011358963682681302}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,999] Trial 189 finished with value: 0.9682755650146954 and parameters: {'n_estimators': 640, 'max_depth': 8, 'learning_rate': 0.3600401699105416, 'gamma': 8.633600075102984e-07, 'min_child_weight': 7, 'subsample': 0.9529371337244095, 'colsample_bytree': 0.5793876812256805, 'reg_alpha': 1.854830942484543e-05, 'reg_lambda': 0.0071807775805754264}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,077] Trial 190 finished with value: 0.9641785750481402 and parameters: {'n_estimators': 580, 'max_depth': 1, 'learning_rate': 0.3955258955416034, 'gamma': 0.0028855432380126994, 'min_child_weight': 1, 'subsample': 0.6558300232658375, 'colsample_bytree': 0.532053023783299, 'reg_alpha': 5.025989847819503e-05, 'reg_lambda': 0.0003699564761924533}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,170] Trial 191 finished with value: 0.9765556906861255 and parameters: {'n_estimators': 575, 'max_depth': 8, 'learning_rate': 0.36859695453147573, 'gamma': 0.00017562327914148257, 'min_child_weight': 1, 'subsample': 0.9949295139298673, 'colsample_bytree': 0.504238342895176, 'reg_alpha': 5.494592850652422e-06, 'reg_lambda': 0.05999590732038283}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,260] Trial 192 finished with value: 0.9762187088274045 and parameters: {'n_estimators': 597, 'max_depth': 8, 'learning_rate': 0.37669387399080473, 'gamma': 0.0001054246260196604, 'min_child_weight': 1, 'subsample': 0.9911385292858662, 'colsample_bytree': 0.5008474674992347, 'reg_alpha': 3.775728586579843e-06, 'reg_lambda': 0.06070795069378114}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,338] Trial 193 finished with value: 0.9697603121516163 and parameters: {'n_estimators': 565, 'max_depth': 8, 'learning_rate': 0.3733367211586875, 'gamma': 0.00010171868639087341, 'min_child_weight': 1, 'subsample': 0.9885402527271766, 'colsample_bytree': 0.503296796362895, 'reg_alpha': 3.156842485650543e-06, 'reg_lambda': 0.10114525177731656}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,432] Trial 194 finished with value: 0.9722965440356746 and parameters: {'n_estimators': 618, 'max_depth': 9, 'learning_rate': 0.36465218306972474, 'gamma': 0.000132198680326127, 'min_child_weight': 1, 'subsample': 0.9998270693902586, 'colsample_bytree': 0.5003410098501623, 'reg_alpha': 5.171884685209688e-06, 'reg_lambda': 0.048537409450488525}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,524] Trial 195 finished with value: 0.9762187088274045 and parameters: {'n_estimators': 699, 'max_depth': 8, 'learning_rate': 0.3840175223825088, 'gamma': 2.8688603044497538e-05, 'min_child_weight': 1, 'subsample': 0.9791585243331079, 'colsample_bytree': 0.5177740106795239, 'reg_alpha': 1.985570244508912e-06, 'reg_lambda': 0.0850937565995448}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,616] Trial 196 finished with value: 0.9731351981351981 and parameters: {'n_estimators': 704, 'max_depth': 8, 'learning_rate': 0.3845510622747572, 'gamma': 3.2293045599745385e-05, 'min_child_weight': 1, 'subsample': 0.9708751000446808, 'colsample_bytree': 0.5160888376342883, 'reg_alpha': 1.1285147244308468e-06, 'reg_lambda': 0.07777113981412653}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,707] Trial 197 finished with value: 0.9740194588020676 and parameters: {'n_estimators': 686, 'max_depth': 7, 'learning_rate': 0.3807493855934895, 'gamma': 4.962483143323837e-05, 'min_child_weight': 1, 'subsample': 0.9825848909958048, 'colsample_bytree': 0.5164570385938616, 'reg_alpha': 2.365763358102613e-06, 'reg_lambda': 0.13749590646470938}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,799] Trial 198 finished with value: 0.9669251038816256 and parameters: {'n_estimators': 679, 'max_depth': 7, 'learning_rate': 0.39587927481041185, 'gamma': 6.076559520990681e-06, 'min_child_weight': 2, 'subsample': 0.980027070691821, 'colsample_bytree': 0.5121661148934848, 'reg_alpha': 2.1636220457836166e-06, 'reg_lambda': 0.1981344625178931}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,894] Trial 199 finished with value: 0.9730085132259045 and parameters: {'n_estimators': 734, 'max_depth': 8, 'learning_rate': 0.3827459493351444, 'gamma': 5.577111965000543e-05, 'min_child_weight': 1, 'subsample': 0.9874622359136933, 'colsample_bytree': 0.524715757741188, 'reg_alpha': 2.583619561021487e-06, 'reg_lambda': 0.12564000314896498}. Best is trial 87 with value: 0.9775793047532177.\n" ] }, { @@ -250,17 +790,17 @@ "output_type": "stream", "text": [ "Best trial:\n", - "F1 Score: 0.721809\n", + "F1 Score: 0.977579\n", "Parameters:\n", - "n_estimators: 395\n", - "max_depth: 14\n", - "learning_rate: 0.5516744736853054\n", - "gamma: 0.06586236308160907\n", - "min_child_weight: 7\n", - "subsample: 0.934260221749137\n", - "colsample_bytree: 0.5657192375418623\n", - "reg_alpha: 0.0004839456623687217\n", - "reg_lambda: 0.024086595827121155\n" + "n_estimators: 636\n", + "max_depth: 3\n", + "learning_rate: 0.28911459468011935\n", + "gamma: 0.0026877179567177173\n", + "min_child_weight: 1\n", + "subsample: 0.9884898945689472\n", + "colsample_bytree: 0.5529899112143574\n", + "reg_alpha: 8.780578569353003e-06\n", + "reg_lambda: 0.024175358439225716\n" ] } ], @@ -283,7 +823,6 @@ " \"reg_lambda\": trial.suggest_float(\"reg_lambda\", 1e-8, 1.0, log=True),\n", " \"enable_categorical\": True,\n", " \"eval_metric\": \"logloss\",\n", - " \"verbosity\": 0,\n", " }\n", "\n", " model = xgb.XGBClassifier(**params)\n", @@ -321,40 +860,136 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "[I 2025-07-28 20:39:17,046] A new study created in memory with name: no-name-d640d2f2-b93d-4408-a7ea-9161e95491e3\n", - "[I 2025-07-28 20:39:17,550] Trial 0 finished with value: 0.6231313020966095 and parameters: {'boosting_type': 'goss', 'num_leaves': 157, 'learning_rate': 0.011930732887702704, 'n_estimators': 104, 'max_depth': 8, 'min_child_samples': 71, 'subsample': 0.9402086280771477, 'colsample_bytree': 0.7682647640164344, 'reg_alpha': 1.4241168044547617e-08, 'reg_lambda': 2.0676712941542342e-07, 'min_split_gain': 0.0033415036895292826, 'cat_smooth': 97, 'cat_l2': 0.6970465070605171}. Best is trial 0 with value: 0.6231313020966095.\n", - "[I 2025-07-28 20:39:32,638] Trial 1 finished with value: 0.6231313020966095 and parameters: {'boosting_type': 'dart', 'num_leaves': 175, 'learning_rate': 0.0023119406442152646, 'n_estimators': 824, 'max_depth': 8, 'min_child_samples': 45, 'subsample': 0.9676678537059415, 'colsample_bytree': 0.5552007172897914, 'reg_alpha': 2.556389565074754e-07, 'reg_lambda': 1.8954788415197908e-06, 'min_split_gain': 9.567889959044472e-08, 'cat_smooth': 8, 'cat_l2': 0.012629197180178365}. Best is trial 0 with value: 0.6231313020966095.\n", - "...", - "[I 2025-07-28 21:09:32,868] Trial 199 finished with value: 0.7127633201595156 and parameters: {'boosting_type': 'dart', 'num_leaves': 144, 'learning_rate': 0.012575812659743247, 'n_estimators': 549, 'max_depth': 11, 'min_child_samples': 33, 'subsample': 0.8201396579082235, 'colsample_bytree': 0.8618094826946774, 'reg_alpha': 0.00022277139513162425, 'reg_lambda': 1.2026457556920858, 'min_split_gain': 9.340322067132456e-08, 'cat_smooth': 78, 'cat_l2': 9.351735111010793}. Best is trial 137 with value: 0.7338329002847149.\n" + "[I 2025-08-18 21:38:31,112] A new study created in memory with name: no-name-a2c71fbc-43fe-4d55-a82d-10f7362f12f0\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[W 2025-08-18 21:38:31,823] Trial 0 failed with parameters: {'boosting_type': 'gbdt', 'num_leaves': 231, 'learning_rate': 0.004729326807185178, 'n_estimators': 180, 'max_depth': 15, 'min_child_samples': 62, 'subsample': 0.95535818357979, 'colsample_bytree': 0.7438374709143218, 'reg_alpha': 1.0331517436951706e-05, 'reg_lambda': 1.2172287308521004e-05, 'min_split_gain': 4.144384519107149e-06, 'cat_smooth': 47, 'cat_l2': 2.5374071883620803e-07} because of the following error: ValueError('\\nAll the 10 fits failed.\\nIt is very likely that your model is misconfigured.\\nYou can try to debug the error by setting error_score=\\'raise\\'.\\n\\nBelow are more details about the failures:\\n--------------------------------------------------------------------------------\\n10 fits failed with the following error:\\nTraceback (most recent call last):\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\\n estimator.fit(X_train, y_train, **fit_params)\\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\\n super().fit(\\n ~~~~~~~~~~~^\\n X,\\n ^^\\n ...<12 lines>...\\n init_model=init_model,\\n ^^^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\\n self._Booster = train(\\n ~~~~~^\\n params=params,\\n ^^^^^^^^^^^^^^\\n ...<6 lines>...\\n callbacks=callbacks,\\n ^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\\n booster = Booster(params=params, train_set=train_set)\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\\n train_set.construct()\\n ~~~~~~~~~~~~~~~~~~~^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\\n self._lazy_init(\\n ~~~~~~~~~~~~~~~^\\n data=self.data,\\n ^^^^^^^^^^^^^^^\\n ...<9 lines>...\\n position=self.position,\\n ^^^^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\\n return self.set_feature_name(feature_name)\\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\\n _safe_call(\\n ~~~~~~~~~~^\\n _LIB.LGBM_DatasetSetFeatureNames(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n ...<3 lines>...\\n )\\n ^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\\n').\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py\", line 201, in _run_trial\n", + " value_or_values = func(trial)\n", + " File \"/var/folders/dj/6m_rn6_56pvb0zb7k0t6bz4r0000gn/T/ipykernel_47070/4223881388.py\", line 28, in objective\n", + " scores = cross_val_score(\n", + " estimator=model,\n", + " ...<4 lines>...\n", + " n_jobs=-1,\n", + " )\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py\", line 216, in wrapper\n", + " return func(*args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 684, in cross_val_score\n", + " cv_results = cross_validate(\n", + " estimator=estimator,\n", + " ...<9 lines>...\n", + " error_score=error_score,\n", + " )\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py\", line 216, in wrapper\n", + " return func(*args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 431, in cross_validate\n", + " _warn_or_raise_about_fit_failures(results, error_score)\n", + " ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 517, in _warn_or_raise_about_fit_failures\n", + " raise ValueError(all_fits_failed_message)\n", + "ValueError: \n", + "All the 10 fits failed.\n", + "It is very likely that your model is misconfigured.\n", + "You can try to debug the error by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n", + " super().fit(\n", + " ~~~~~~~~~~~^\n", + " X,\n", + " ^^\n", + " ...<12 lines>...\n", + " init_model=init_model,\n", + " ^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n", + " self._Booster = train(\n", + " ~~~~~^\n", + " params=params,\n", + " ^^^^^^^^^^^^^^\n", + " ...<6 lines>...\n", + " callbacks=callbacks,\n", + " ^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n", + " booster = Booster(params=params, train_set=train_set)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n", + " train_set.construct()\n", + " ~~~~~~~~~~~~~~~~~~~^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n", + " self._lazy_init(\n", + " ~~~~~~~~~~~~~~~^\n", + " data=self.data,\n", + " ^^^^^^^^^^^^^^^\n", + " ...<9 lines>...\n", + " position=self.position,\n", + " ^^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n", + " return self.set_feature_name(feature_name)\n", + " ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n", + " _safe_call(\n", + " ~~~~~~~~~~^\n", + " _LIB.LGBM_DatasetSetFeatureNames(\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " ...<3 lines>...\n", + " )\n", + " ^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n", + " raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\n", + "lightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n", + "\n", + "[W 2025-08-18 21:38:31,824] Trial 0 failed with value None.\n" ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best trial:\n", - "F1 Score: 0.733833\n", - "Parameters:\n", - "boosting_type: dart\n", - "num_leaves: 115\n", - "learning_rate: 0.014925187890769775\n", - "n_estimators: 440\n", - "max_depth: 18\n", - "min_child_samples: 25\n", - "subsample: 0.8388698484023127\n", - "colsample_bytree: 0.871735744058394\n", - "reg_alpha: 0.0002339943750255717\n", - "reg_lambda: 0.008719224583360354\n", - "min_split_gain: 6.975191054445815e-05\n", - "cat_smooth: 52\n", - "cat_l2: 1.870771829368486e-07\n" + "ename": "ValueError", + "evalue": "\nAll the 10 fits failed.\nIt is very likely that your model is misconfigured.\nYou can try to debug the error by setting error_score='raise'.\n\nBelow are more details about the failures:\n--------------------------------------------------------------------------------\n10 fits failed with the following error:\nTraceback (most recent call last):\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n estimator.fit(X_train, y_train, **fit_params)\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n super().fit(\n ~~~~~~~~~~~^\n X,\n ^^\n ...<12 lines>...\n init_model=init_model,\n ^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n self._Booster = train(\n ~~~~~^\n params=params,\n ^^^^^^^^^^^^^^\n ...<6 lines>...\n callbacks=callbacks,\n ^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n booster = Booster(params=params, train_set=train_set)\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n train_set.construct()\n ~~~~~~~~~~~~~~~~~~~^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n self._lazy_init(\n ~~~~~~~~~~~~~~~^\n data=self.data,\n ^^^^^^^^^^^^^^^\n ...<9 lines>...\n position=self.position,\n ^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n return self.set_feature_name(feature_name)\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n _safe_call(\n ~~~~~~~~~~^\n _LIB.LGBM_DatasetSetFeatureNames(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<3 lines>...\n )\n ^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mValueError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 41\u001b[39m\n\u001b[32m 37\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores.mean()\n\u001b[32m 40\u001b[39m study = optuna.create_study(direction=\u001b[33m\"\u001b[39m\u001b[33mmaximize\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m41\u001b[39m \u001b[43mstudy\u001b[49m\u001b[43m.\u001b[49m\u001b[43moptimize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobjective\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m200\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m best_trial = study.best_trial\n\u001b[32m 45\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mBest trial:\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/study.py:489\u001b[39m, in \u001b[36mStudy.optimize\u001b[39m\u001b[34m(self, func, n_trials, timeout, n_jobs, catch, callbacks, gc_after_trial, show_progress_bar)\u001b[39m\n\u001b[32m 387\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34moptimize\u001b[39m(\n\u001b[32m 388\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m 389\u001b[39m func: ObjectiveFuncType,\n\u001b[32m (...)\u001b[39m\u001b[32m 396\u001b[39m show_progress_bar: \u001b[38;5;28mbool\u001b[39m = \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[32m 397\u001b[39m ) -> \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m 398\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Optimize an objective function.\u001b[39;00m\n\u001b[32m 399\u001b[39m \n\u001b[32m 400\u001b[39m \u001b[33;03m Optimization is done by choosing a suitable set of hyperparameter values from a given\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 487\u001b[39m \u001b[33;03m If nested invocation of this method occurs.\u001b[39;00m\n\u001b[32m 488\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m489\u001b[39m \u001b[43m_optimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 490\u001b[39m \u001b[43m \u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 491\u001b[39m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 492\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 493\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 494\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 495\u001b[39m \u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mIterable\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 496\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 497\u001b[39m \u001b[43m \u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 498\u001b[39m \u001b[43m \u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 499\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:64\u001b[39m, in \u001b[36m_optimize\u001b[39m\u001b[34m(study, func, n_trials, timeout, n_jobs, catch, callbacks, gc_after_trial, show_progress_bar)\u001b[39m\n\u001b[32m 62\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 63\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m n_jobs == \u001b[32m1\u001b[39m:\n\u001b[32m---> \u001b[39m\u001b[32m64\u001b[39m \u001b[43m_optimize_sequential\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 65\u001b[39m \u001b[43m \u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 66\u001b[39m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 67\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 68\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 69\u001b[39m \u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 70\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 71\u001b[39m \u001b[43m \u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 72\u001b[39m \u001b[43m \u001b[49m\u001b[43mreseed_sampler_rng\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 73\u001b[39m \u001b[43m \u001b[49m\u001b[43mtime_start\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 74\u001b[39m \u001b[43m \u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 75\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 76\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 77\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m n_jobs == -\u001b[32m1\u001b[39m:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:161\u001b[39m, in \u001b[36m_optimize_sequential\u001b[39m\u001b[34m(study, func, n_trials, timeout, catch, callbacks, gc_after_trial, reseed_sampler_rng, time_start, progress_bar)\u001b[39m\n\u001b[32m 158\u001b[39m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[32m 160\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m161\u001b[39m frozen_trial = \u001b[43m_run_trial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 162\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 163\u001b[39m \u001b[38;5;66;03m# The following line mitigates memory problems that can be occurred in some\u001b[39;00m\n\u001b[32m 164\u001b[39m \u001b[38;5;66;03m# environments (e.g., services that use computing containers such as GitHub Actions).\u001b[39;00m\n\u001b[32m 165\u001b[39m \u001b[38;5;66;03m# Please refer to the following PR for further details:\u001b[39;00m\n\u001b[32m 166\u001b[39m \u001b[38;5;66;03m# https://github.com/optuna/optuna/pull/325.\u001b[39;00m\n\u001b[32m 167\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m gc_after_trial:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:253\u001b[39m, in \u001b[36m_run_trial\u001b[39m\u001b[34m(study, func, catch)\u001b[39m\n\u001b[32m 246\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[33m\"\u001b[39m\u001b[33mShould not reach.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 248\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[32m 249\u001b[39m frozen_trial.state == TrialState.FAIL\n\u001b[32m 250\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m func_err \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 251\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(func_err, catch)\n\u001b[32m 252\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m253\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m func_err\n\u001b[32m 254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m frozen_trial\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:201\u001b[39m, in \u001b[36m_run_trial\u001b[39m\u001b[34m(study, func, catch)\u001b[39m\n\u001b[32m 199\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m get_heartbeat_thread(trial._trial_id, study._storage):\n\u001b[32m 200\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m201\u001b[39m value_or_values = \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrial\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 202\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m exceptions.TrialPruned \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 203\u001b[39m \u001b[38;5;66;03m# TODO(mamu): Handle multi-objective cases.\u001b[39;00m\n\u001b[32m 204\u001b[39m state = TrialState.PRUNED\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 28\u001b[39m, in \u001b[36mobjective\u001b[39m\u001b[34m(trial)\u001b[39m\n\u001b[32m 5\u001b[39m params = {\n\u001b[32m 6\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mobjective\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mbinary\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 7\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmetric\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mbinary_logloss\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 23\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mverbosity\u001b[39m\u001b[33m\"\u001b[39m: -\u001b[32m1\u001b[39m,\n\u001b[32m 24\u001b[39m }\n\u001b[32m 26\u001b[39m model = lgb.LGBMClassifier(**params)\n\u001b[32m---> \u001b[39m\u001b[32m28\u001b[39m scores = \u001b[43mcross_val_score\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 29\u001b[39m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 30\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m=\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 31\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m=\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 32\u001b[39m \u001b[43m \u001b[49m\u001b[43mscoring\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mf1_weighted\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 33\u001b[39m \u001b[43m \u001b[49m\u001b[43mcv\u001b[49m\u001b[43m=\u001b[49m\u001b[43mStratifiedKFold\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_splits\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m10\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshuffle\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrandom_state\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m42\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 34\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 35\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 37\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores.mean()\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py:216\u001b[39m, in \u001b[36mvalidate_params..decorator..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 210\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 211\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 212\u001b[39m skip_parameter_validation=(\n\u001b[32m 213\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 214\u001b[39m )\n\u001b[32m 215\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m216\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 218\u001b[39m \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[32m 219\u001b[39m \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[32m 220\u001b[39m \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[32m 221\u001b[39m \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[32m 222\u001b[39m msg = re.sub(\n\u001b[32m 223\u001b[39m \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[33m\\\u001b[39m\u001b[33mw+ must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 224\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc.\u001b[34m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 225\u001b[39m \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[32m 226\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:684\u001b[39m, in \u001b[36mcross_val_score\u001b[39m\u001b[34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, params, pre_dispatch, error_score)\u001b[39m\n\u001b[32m 681\u001b[39m \u001b[38;5;66;03m# To ensure multimetric format is not supported\u001b[39;00m\n\u001b[32m 682\u001b[39m scorer = check_scoring(estimator, scoring=scoring)\n\u001b[32m--> \u001b[39m\u001b[32m684\u001b[39m cv_results = \u001b[43mcross_validate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 685\u001b[39m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m=\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 686\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m=\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 687\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m=\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 688\u001b[39m \u001b[43m \u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 689\u001b[39m \u001b[43m \u001b[49m\u001b[43mscoring\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mscore\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mscorer\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 690\u001b[39m \u001b[43m \u001b[49m\u001b[43mcv\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 691\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 692\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 693\u001b[39m \u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[43m=\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 694\u001b[39m \u001b[43m \u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 695\u001b[39m \u001b[43m \u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m=\u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 696\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 697\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cv_results[\u001b[33m\"\u001b[39m\u001b[33mtest_score\u001b[39m\u001b[33m\"\u001b[39m]\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py:216\u001b[39m, in \u001b[36mvalidate_params..decorator..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 210\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 211\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 212\u001b[39m skip_parameter_validation=(\n\u001b[32m 213\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 214\u001b[39m )\n\u001b[32m 215\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m216\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 218\u001b[39m \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[32m 219\u001b[39m \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[32m 220\u001b[39m \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[32m 221\u001b[39m \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[32m 222\u001b[39m msg = re.sub(\n\u001b[32m 223\u001b[39m \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[33m\\\u001b[39m\u001b[33mw+ must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 224\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc.\u001b[34m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 225\u001b[39m \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[32m 226\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:431\u001b[39m, in \u001b[36mcross_validate\u001b[39m\u001b[34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, params, pre_dispatch, return_train_score, return_estimator, return_indices, error_score)\u001b[39m\n\u001b[32m 410\u001b[39m parallel = Parallel(n_jobs=n_jobs, verbose=verbose, pre_dispatch=pre_dispatch)\n\u001b[32m 411\u001b[39m results = parallel(\n\u001b[32m 412\u001b[39m delayed(_fit_and_score)(\n\u001b[32m 413\u001b[39m clone(estimator),\n\u001b[32m (...)\u001b[39m\u001b[32m 428\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m train, test \u001b[38;5;129;01min\u001b[39;00m indices\n\u001b[32m 429\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m431\u001b[39m \u001b[43m_warn_or_raise_about_fit_failures\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresults\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 433\u001b[39m \u001b[38;5;66;03m# For callable scoring, the return type is only know after calling. If the\u001b[39;00m\n\u001b[32m 434\u001b[39m \u001b[38;5;66;03m# return type is a dictionary, the error scores can now be inserted with\u001b[39;00m\n\u001b[32m 435\u001b[39m \u001b[38;5;66;03m# the correct key.\u001b[39;00m\n\u001b[32m 436\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcallable\u001b[39m(scoring):\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:517\u001b[39m, in \u001b[36m_warn_or_raise_about_fit_failures\u001b[39m\u001b[34m(results, error_score)\u001b[39m\n\u001b[32m 510\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m num_failed_fits == num_fits:\n\u001b[32m 511\u001b[39m all_fits_failed_message = (\n\u001b[32m 512\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mAll the \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m fits failed.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 513\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mIt is very likely that your model is misconfigured.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 514\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mYou can try to debug the error by setting error_score=\u001b[39m\u001b[33m'\u001b[39m\u001b[33mraise\u001b[39m\u001b[33m'\u001b[39m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 515\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mBelow are more details about the failures:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mfit_errors_summary\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 516\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m517\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(all_fits_failed_message)\n\u001b[32m 519\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 520\u001b[39m some_fits_failed_message = (\n\u001b[32m 521\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mnum_failed_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m fits failed out of a total of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 522\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mThe score on these train-test partitions for these parameters\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m (...)\u001b[39m\u001b[32m 526\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mBelow are more details about the failures:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mfit_errors_summary\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 527\u001b[39m )\n", + "\u001b[31mValueError\u001b[39m: \nAll the 10 fits failed.\nIt is very likely that your model is misconfigured.\nYou can try to debug the error by setting error_score='raise'.\n\nBelow are more details about the failures:\n--------------------------------------------------------------------------------\n10 fits failed with the following error:\nTraceback (most recent call last):\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n estimator.fit(X_train, y_train, **fit_params)\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n super().fit(\n ~~~~~~~~~~~^\n X,\n ^^\n ...<12 lines>...\n init_model=init_model,\n ^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n self._Booster = train(\n ~~~~~^\n params=params,\n ^^^^^^^^^^^^^^\n ...<6 lines>...\n callbacks=callbacks,\n ^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n booster = Booster(params=params, train_set=train_set)\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n train_set.construct()\n ~~~~~~~~~~~~~~~~~~~^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n self._lazy_init(\n ~~~~~~~~~~~~~~~^\n data=self.data,\n ^^^^^^^^^^^^^^^\n ...<9 lines>...\n position=self.position,\n ^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n return self.set_feature_name(feature_name)\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n _safe_call(\n ~~~~~~~~~~^\n _LIB.LGBM_DatasetSetFeatureNames(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<3 lines>...\n )\n ^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n" ] } ], @@ -419,18 +1054,216 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "[I 2025-07-28 21:10:05,884] A new study created in memory with name: no-name-bf4ade11-fdd4-4e51-8e36-3ce62bb0ef30\n", - "[I 2025-07-28 21:10:06,304] Trial 0 finished with value: 0.644865039962623 and parameters: {'iterations': 326, 'depth': 10, 'learning_rate': 0.19634246718523193, 'l2_leaf_reg': 2.874223428781629e-05, 'random_strength': 0.0007132910532975053, 'bagging_temperature': 4.68236671244208, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.851641906909135}. Best is trial 0 with value: 0.644865039962623.\n", - "[I 2025-07-28 21:10:06,587] Trial 1 finished with value: 0.6769947086440917 and parameters: {'iterations': 364, 'depth': 13, 'learning_rate': 0.04465629029593174, 'l2_leaf_reg': 1.3554273893773743e-08, 'random_strength': 0.4601972154575927, 'bagging_temperature': 1.856284401555177, 'border_count': 182, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 33, 'rsm': 0.27841739352654576}. Best is trial 1 with value: 0.6769947086440917.\n", - "...", - "[I 2025-07-28 21:10:22,377] Trial 199 finished with value: 0.713373121188903 and parameters: {'iterations': 161, 'depth': 2, 'learning_rate': 0.007216156705027904, 'l2_leaf_reg': 4.2665020699161245e-07, 'random_strength': 0.00017324894641089118, 'bagging_temperature': 0.4153387841633685, 'border_count': 96, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.8596971617051177}. Best is trial 94 with value: 0.7319447527560347.\n" + "[I 2025-08-17 17:05:16,870] A new study created in memory with name: no-name-58367467-9a1e-4d65-bfaf-46562a4f4de8\n", + "[I 2025-08-17 17:05:17,646] Trial 0 finished with value: 0.9336826514116986 and parameters: {'iterations': 447, 'depth': 7, 'learning_rate': 0.010022052741993987, 'l2_leaf_reg': 0.00012108855576002585, 'random_strength': 0.0014307171606371407, 'bagging_temperature': 1.2400472888236214, 'border_count': 118, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 67, 'rsm': 0.7492964415768959}. Best is trial 0 with value: 0.9336826514116986.\n", + "[I 2025-08-17 17:05:28,392] Trial 1 finished with value: 0.9357671816047922 and parameters: {'iterations': 320, 'depth': 12, 'learning_rate': 0.005265584834540258, 'l2_leaf_reg': 3.348332251065364e-05, 'random_strength': 0.016130126681163013, 'bagging_temperature': 3.184610728695145, 'border_count': 132, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 16, 'rsm': 0.3661804580910256}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:05:56,176] Trial 2 finished with value: 0.9353286370472839 and parameters: {'iterations': 301, 'depth': 15, 'learning_rate': 0.001229239587857227, 'l2_leaf_reg': 0.24114858700166839, 'random_strength': 3.653421601255403e-08, 'bagging_temperature': 0.268499084758938, 'border_count': 38, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 87, 'rsm': 0.4077894430643999}. Best is trial 1 with value: 0.9357671816047922.\n", + "/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/joblib/externals/loky/process_executor.py:782: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n", + " warnings.warn(\n", + "[I 2025-08-17 17:05:59,001] Trial 3 finished with value: 0.9263914470949277 and parameters: {'iterations': 308, 'depth': 8, 'learning_rate': 0.006923745139831324, 'l2_leaf_reg': 2.232447055025466e-05, 'random_strength': 9.589017869992023, 'bagging_temperature': 1.1664981735070379, 'border_count': 244, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 36, 'rsm': 0.2272363033800584}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:05:59,894] Trial 4 finished with value: 0.9307067517478776 and parameters: {'iterations': 384, 'depth': 2, 'learning_rate': 0.006162982787165949, 'l2_leaf_reg': 0.0002455528925686078, 'random_strength': 0.00023861190911366858, 'bagging_temperature': 4.590603297409774, 'border_count': 89, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 43, 'rsm': 0.47744937225955014}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:09:58,626] Trial 5 finished with value: 0.9211242467721258 and parameters: {'iterations': 126, 'depth': 16, 'learning_rate': 0.009746370340105637, 'l2_leaf_reg': 0.00030954644505648175, 'random_strength': 2.429275544391415e-05, 'bagging_temperature': 2.010716645408075, 'border_count': 49, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 13, 'rsm': 0.9165484726032328}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:00,013] Trial 6 finished with value: 0.9279980893054489 and parameters: {'iterations': 304, 'depth': 13, 'learning_rate': 0.002452909941863272, 'l2_leaf_reg': 0.0007960036275127577, 'random_strength': 0.03279083919638105, 'bagging_temperature': 0.11620956490151985, 'border_count': 176, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 90, 'rsm': 0.4918546771049915}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:00,157] Trial 7 finished with value: 0.9033264977789675 and parameters: {'iterations': 118, 'depth': 6, 'learning_rate': 0.0010815676236105107, 'l2_leaf_reg': 2.343577077870732e-06, 'random_strength': 0.19573002126091082, 'bagging_temperature': 9.328816805466154, 'border_count': 92, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 73, 'rsm': 0.7721304474012315}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:01,029] Trial 8 finished with value: 0.9282028882177922 and parameters: {'iterations': 139, 'depth': 13, 'learning_rate': 0.37449386293043335, 'l2_leaf_reg': 1.510385273200855e-07, 'random_strength': 8.805885915613816e-06, 'bagging_temperature': 9.920620684320985, 'border_count': 103, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 82, 'rsm': 0.7133460589949088}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:01,332] Trial 9 finished with value: 0.9478823107512284 and parameters: {'iterations': 442, 'depth': 14, 'learning_rate': 0.017390550482273417, 'l2_leaf_reg': 1.4191517744514907e-08, 'random_strength': 0.08085481833131353, 'bagging_temperature': 0.5861540758081338, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.3057024492058511}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:01,540] Trial 10 finished with value: 0.9387675439474699 and parameters: {'iterations': 483, 'depth': 10, 'learning_rate': 0.06649646241149486, 'l2_leaf_reg': 1.5294498702948475e-08, 'random_strength': 6.457056903771226, 'bagging_temperature': 0.3762360484331467, 'border_count': 185, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 60, 'rsm': 0.1129456685393378}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:01,745] Trial 11 finished with value: 0.9364695961754009 and parameters: {'iterations': 488, 'depth': 10, 'learning_rate': 0.07157332063575793, 'l2_leaf_reg': 1.2340552291844822e-08, 'random_strength': 6.8475165988578945, 'bagging_temperature': 0.41833481531429084, 'border_count': 183, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 57, 'rsm': 0.12225677733328608}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:01,879] Trial 12 finished with value: 0.9420281633568404 and parameters: {'iterations': 401, 'depth': 10, 'learning_rate': 0.04705474327284803, 'l2_leaf_reg': 4.619135274034043e-08, 'random_strength': 0.2877962903926624, 'bagging_temperature': 0.4410061869425525, 'border_count': 183, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.10497821047560195}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,057] Trial 13 finished with value: 0.9392165631469979 and parameters: {'iterations': 401, 'depth': 4, 'learning_rate': 0.035092587572258575, 'l2_leaf_reg': 7.418402902502616e-07, 'random_strength': 0.24279060329838162, 'bagging_temperature': 0.550265277142082, 'border_count': 223, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.2912361775318139}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,163] Trial 14 finished with value: 0.9332145859168754 and parameters: {'iterations': 196, 'depth': 11, 'learning_rate': 0.20424392007978667, 'l2_leaf_reg': 0.07259273690884574, 'random_strength': 0.445044262919236, 'bagging_temperature': 0.16497562046877015, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.2189011845729476}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,465] Trial 15 finished with value: 0.942245284348707 and parameters: {'iterations': 396, 'depth': 14, 'learning_rate': 0.023781291427423204, 'l2_leaf_reg': 9.270565187606277, 'random_strength': 0.0038796338897692183, 'bagging_temperature': 0.6361579144475542, 'border_count': 205, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 77, 'rsm': 0.29776900392803746}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,727] Trial 16 finished with value: 0.9394832914849566 and parameters: {'iterations': 234, 'depth': 14, 'learning_rate': 0.025406716067111187, 'l2_leaf_reg': 0.00940902288686199, 'random_strength': 0.0011467692702004809, 'bagging_temperature': 0.9288491682156569, 'border_count': 217, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 79, 'rsm': 0.3312745395954699}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:03,328] Trial 17 finished with value: 0.9364990440949738 and parameters: {'iterations': 364, 'depth': 16, 'learning_rate': 0.01459315336705923, 'l2_leaf_reg': 1.5017720263656562, 'random_strength': 2.168129156965766e-07, 'bagging_temperature': 0.7031608622072022, 'border_count': 161, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 68, 'rsm': 0.579429591294561}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:04,579] Trial 18 finished with value: 0.9336769052166423 and parameters: {'iterations': 437, 'depth': 14, 'learning_rate': 0.09335993870933126, 'l2_leaf_reg': 0.009070739751415742, 'random_strength': 0.011596516896850755, 'bagging_temperature': 0.21831142466765102, 'border_count': 217, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 31, 'rsm': 0.6254526681385288}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:04,966] Trial 19 finished with value: 0.9452204073242001 and parameters: {'iterations': 345, 'depth': 12, 'learning_rate': 0.018942551364461224, 'l2_leaf_reg': 7.3406357956098915, 'random_strength': 7.810547328849867e-05, 'bagging_temperature': 2.592739930745042, 'border_count': 254, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 51, 'rsm': 0.2411083987489646}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:05,836] Trial 20 finished with value: 0.9416257250171322 and parameters: {'iterations': 238, 'depth': 12, 'learning_rate': 0.16297331414932478, 'l2_leaf_reg': 3.20532030293621e-06, 'random_strength': 2.667508753112458e-05, 'bagging_temperature': 1.9944880335976674, 'border_count': 248, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 1, 'rsm': 0.19965980630801725}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:06,233] Trial 21 finished with value: 0.9394580121286875 and parameters: {'iterations': 354, 'depth': 14, 'learning_rate': 0.021032869203904486, 'l2_leaf_reg': 8.092710664822752, 'random_strength': 0.0001705884950621921, 'bagging_temperature': 2.0769627719799915, 'border_count': 204, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 50, 'rsm': 0.2886138656825273}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:06,725] Trial 22 finished with value: 0.9422897581604335 and parameters: {'iterations': 427, 'depth': 12, 'learning_rate': 0.01728066242461722, 'l2_leaf_reg': 8.28487233199894, 'random_strength': 2.149716909747561e-06, 'bagging_temperature': 0.8352506132748097, 'border_count': 251, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 75, 'rsm': 0.42775896559818366}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:06,823] Trial 23 finished with value: 0.9278465391707099 and parameters: {'iterations': 54, 'depth': 9, 'learning_rate': 0.0034815878598868596, 'l2_leaf_reg': 0.5205208963206108, 'random_strength': 1.4520874032939126e-06, 'bagging_temperature': 4.7210870436758015, 'border_count': 255, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 56, 'rsm': 0.4280559895016039}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:07,101] Trial 24 finished with value: 0.9479595700629927 and parameters: {'iterations': 439, 'depth': 11, 'learning_rate': 0.014527673079264242, 'l2_leaf_reg': 0.04052582749131081, 'random_strength': 7.707152529842055e-07, 'bagging_temperature': 1.0117939040088955, 'border_count': 66, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 66, 'rsm': 0.5153902213295005}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:07,491] Trial 25 finished with value: 0.9363015933085312 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.011466713691318525, 'l2_leaf_reg': 0.07842092575522967, 'random_strength': 1.622972705803686e-08, 'bagging_temperature': 1.328255947976371, 'border_count': 67, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 48, 'rsm': 0.536170510768572}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:07,817] Trial 26 finished with value: 0.9335191724299957 and parameters: {'iterations': 461, 'depth': 9, 'learning_rate': 0.0429759330516577, 'l2_leaf_reg': 0.004048148753961586, 'random_strength': 3.7632379882557923e-07, 'bagging_temperature': 3.403927830806352, 'border_count': 69, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 64, 'rsm': 0.6525305409485735}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:08,358] Trial 27 finished with value: 0.9282013843144794 and parameters: {'iterations': 350, 'depth': 6, 'learning_rate': 0.003882869945542356, 'l2_leaf_reg': 0.05588647211639355, 'random_strength': 6.359930947232507e-05, 'bagging_temperature': 1.4592262498420976, 'border_count': 131, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 34, 'rsm': 0.9793885580992495}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:08,548] Trial 28 finished with value: 0.9420309049149707 and parameters: {'iterations': 425, 'depth': 11, 'learning_rate': 0.029726236281782142, 'l2_leaf_reg': 1.5338456392901354, 'random_strength': 3.743821948231872e-06, 'bagging_temperature': 2.9080001491398706, 'border_count': 62, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 44, 'rsm': 0.17938436731862395}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:08,873] Trial 29 finished with value: 0.9422389645096398 and parameters: {'iterations': 464, 'depth': 13, 'learning_rate': 0.009239537495248366, 'l2_leaf_reg': 0.0016581052501387665, 'random_strength': 0.0010903132600641387, 'bagging_temperature': 5.8823898983566085, 'border_count': 117, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 68, 'rsm': 0.369621859571436}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:09,187] Trial 30 finished with value: 0.9396483121154722 and parameters: {'iterations': 330, 'depth': 8, 'learning_rate': 0.014443547745130356, 'l2_leaf_reg': 1.439392094711217, 'random_strength': 3.739301341196257e-07, 'bagging_temperature': 0.308963668790458, 'border_count': 111, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 85, 'rsm': 0.8015034073072183}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:09,647] Trial 31 finished with value: 0.9364292909269782 and parameters: {'iterations': 431, 'depth': 12, 'learning_rate': 0.016172687028915955, 'l2_leaf_reg': 9.851796326883738, 'random_strength': 1.5263901772318894e-06, 'bagging_temperature': 0.8713768131029922, 'border_count': 236, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 71, 'rsm': 0.46762344504636993}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:10,098] Trial 32 finished with value: 0.9420281633568404 and parameters: {'iterations': 422, 'depth': 12, 'learning_rate': 0.019237803571276867, 'l2_leaf_reg': 5.64247056264795e-05, 'random_strength': 1.110832663151052e-07, 'bagging_temperature': 0.769726648591094, 'border_count': 234, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 62, 'rsm': 0.3888529760016267}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:45,302] Trial 33 finished with value: 0.938692385540542 and parameters: {'iterations': 463, 'depth': 15, 'learning_rate': 0.009645280889137171, 'l2_leaf_reg': 0.35813648095480866, 'random_strength': 2.6469075432648367e-06, 'bagging_temperature': 0.5215296142925352, 'border_count': 130, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 76, 'rsm': 0.5297182093386201}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:46,696] Trial 34 finished with value: 0.941986075759133 and parameters: {'iterations': 382, 'depth': 15, 'learning_rate': 0.007461286652302521, 'l2_leaf_reg': 0.045944207061274785, 'random_strength': 1.1780126052966517e-05, 'bagging_temperature': 1.1591340186781007, 'border_count': 35, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 54, 'rsm': 0.4292186056059847}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:54,557] Trial 35 finished with value: 0.938692385540542 and parameters: {'iterations': 323, 'depth': 12, 'learning_rate': 0.005100615830139832, 'l2_leaf_reg': 2.76900031010676, 'random_strength': 4.188228359346592e-08, 'bagging_temperature': 1.747951669619372, 'border_count': 146, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 91, 'rsm': 0.26684788997918296}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:55,361] Trial 36 finished with value: 0.9302795905288737 and parameters: {'iterations': 253, 'depth': 1, 'learning_rate': 0.039079338269258676, 'l2_leaf_reg': 0.3264818328644774, 'random_strength': 0.0001884997641458613, 'bagging_temperature': 2.7785286733195584, 'border_count': 201, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 65, 'rsm': 0.583038894597953}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:58:22,055] Trial 37 finished with value: 0.9388894809828734 and parameters: {'iterations': 280, 'depth': 13, 'learning_rate': 0.014094418061125095, 'l2_leaf_reg': 3.908286333679212, 'random_strength': 8.958686737872702e-05, 'bagging_temperature': 1.032578356936754, 'border_count': 237, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 42, 'rsm': 0.3272909714423266}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:58:23,234] Trial 38 finished with value: 0.9364990440949738 and parameters: {'iterations': 365, 'depth': 11, 'learning_rate': 0.060059916793946344, 'l2_leaf_reg': 7.868576296018248e-06, 'random_strength': 6.792612118084799e-07, 'bagging_temperature': 1.5912784757409366, 'border_count': 166, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.4652304438594406}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:58:24,209] Trial 39 finished with value: 0.9366516728480241 and parameters: {'iterations': 446, 'depth': 7, 'learning_rate': 0.002658865746535032, 'l2_leaf_reg': 0.00011552756384141058, 'random_strength': 0.0005168873823892629, 'bagging_temperature': 0.2564675614174855, 'border_count': 79, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 83, 'rsm': 0.16741994023948076}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:40,334] Trial 40 finished with value: 0.9145144021182363 and parameters: {'iterations': 416, 'depth': 16, 'learning_rate': 0.001625377939477702, 'l2_leaf_reg': 0.01695192283696182, 'random_strength': 1.2800588262812822, 'bagging_temperature': 2.460206131631878, 'border_count': 44, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 28, 'rsm': 0.35901664766904245}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:42,002] Trial 41 finished with value: 0.9392165631469979 and parameters: {'iterations': 389, 'depth': 15, 'learning_rate': 0.025079439069078373, 'l2_leaf_reg': 0.6243249540865272, 'random_strength': 0.006997599154730658, 'bagging_temperature': 0.5911520319919781, 'border_count': 198, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.25415982233413037}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:42,934] Trial 42 finished with value: 0.9392165631469979 and parameters: {'iterations': 406, 'depth': 13, 'learning_rate': 0.02054123087754466, 'l2_leaf_reg': 3.919564761634939, 'random_strength': 0.055677410426894, 'bagging_temperature': 0.6517074553530903, 'border_count': 225, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 77, 'rsm': 0.3298616390415405}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:43,845] Trial 43 finished with value: 0.942125092874029 and parameters: {'iterations': 378, 'depth': 14, 'learning_rate': 0.007026342264096326, 'l2_leaf_reg': 8.711730483641022, 'random_strength': 0.00472664123555551, 'bagging_temperature': 0.3446434221110068, 'border_count': 255, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.4312689437069658}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:44,922] Trial 44 finished with value: 0.9450707105413858 and parameters: {'iterations': 473, 'depth': 10, 'learning_rate': 0.027681440661557893, 'l2_leaf_reg': 0.18291973999173342, 'random_strength': 0.00325240166416229, 'bagging_temperature': 0.4897789674798157, 'border_count': 210, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.4990356400478725}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:45,274] Trial 45 finished with value: 0.9448535895495193 and parameters: {'iterations': 479, 'depth': 10, 'learning_rate': 0.029930321385175925, 'l2_leaf_reg': 0.18263997781920413, 'random_strength': 7.949010143906268e-06, 'bagging_temperature': 0.4895403089803191, 'border_count': 96, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.5238484162127857}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:45,768] Trial 46 finished with value: 0.9364356107660455 and parameters: {'iterations': 482, 'depth': 10, 'learning_rate': 0.10487991736828609, 'l2_leaf_reg': 0.14015721097061587, 'random_strength': 0.06871745384141728, 'bagging_temperature': 0.498601333720442, 'border_count': 92, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 59, 'rsm': 0.718638239457858}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:46,074] Trial 47 finished with value: 0.9363079131475986 and parameters: {'iterations': 474, 'depth': 9, 'learning_rate': 0.05448482436597816, 'l2_leaf_reg': 0.0007508312150194058, 'random_strength': 1.979400992759582e-05, 'bagging_temperature': 0.21002891587474082, 'border_count': 53, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 70, 'rsm': 0.6263174952857236}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:46,353] Trial 48 finished with value: 0.936230298491723 and parameters: {'iterations': 449, 'depth': 7, 'learning_rate': 0.03372017360451665, 'l2_leaf_reg': 0.02508232620466937, 'random_strength': 0.02516944698482475, 'bagging_temperature': 0.40295412254807156, 'border_count': 78, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 53, 'rsm': 0.5170308825970374}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:46,687] Trial 49 finished with value: 0.9448535895495193 and parameters: {'iterations': 491, 'depth': 10, 'learning_rate': 0.029047803839886373, 'l2_leaf_reg': 0.12411530275943795, 'random_strength': 8.287968664356238e-06, 'bagging_temperature': 0.46420002877368444, 'border_count': 99, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.576394702785206}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:47,079] Trial 50 finished with value: 0.9335149171108468 and parameters: {'iterations': 449, 'depth': 8, 'learning_rate': 0.012384714014048469, 'l2_leaf_reg': 4.3977186402650976e-07, 'random_strength': 0.002271373832260034, 'bagging_temperature': 0.1043542172721108, 'border_count': 82, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 61, 'rsm': 0.8253111118684651}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:47,501] Trial 51 finished with value: 0.9452420510109686 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.03232589786063133, 'l2_leaf_reg': 0.19703798265346817, 'random_strength': 5.682342586106171e-06, 'bagging_temperature': 0.4457314732827191, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.5727499927098123}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:48,019] Trial 52 finished with value: 0.9448457718455867 and parameters: {'iterations': 499, 'depth': 11, 'learning_rate': 0.08201361984215827, 'l2_leaf_reg': 0.002668078344401463, 'random_strength': 7.629588890045705e-06, 'bagging_temperature': 0.37097420807829845, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 86, 'rsm': 0.6786931996465365}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:48,422] Trial 53 finished with value: 0.9451013583702761 and parameters: {'iterations': 476, 'depth': 11, 'learning_rate': 0.04256451322092073, 'l2_leaf_reg': 0.18609798645826242, 'random_strength': 4.354965293869604e-05, 'bagging_temperature': 0.2870688189555022, 'border_count': 118, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.4929604048578121}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:48,908] Trial 54 finished with value: 0.9422897581604335 and parameters: {'iterations': 464, 'depth': 13, 'learning_rate': 0.04639776081891739, 'l2_leaf_reg': 0.7666153446391908, 'random_strength': 7.476609311900428e-05, 'bagging_temperature': 0.18093394455307654, 'border_count': 122, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.4812218350798194}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:49,360] Trial 55 finished with value: 0.9420419893396765 and parameters: {'iterations': 444, 'depth': 11, 'learning_rate': 0.12177647073574174, 'l2_leaf_reg': 0.025253511131175507, 'random_strength': 0.0004968302143202226, 'bagging_temperature': 0.29574922923916513, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.5800214751972506}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:49,481] Trial 56 finished with value: 0.9303835174168823 and parameters: {'iterations': 179, 'depth': 9, 'learning_rate': 0.4804592339834937, 'l2_leaf_reg': 4.29374260688016e-08, 'random_strength': 2.1023104425356554e-05, 'bagging_temperature': 0.15252719973624834, 'border_count': 189, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.23538528068494383}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:49,935] Trial 57 finished with value: 0.9391606495664544 and parameters: {'iterations': 409, 'depth': 12, 'learning_rate': 0.03858242532556046, 'l2_leaf_reg': 0.0005243163656055302, 'random_strength': 0.90882557493314, 'bagging_temperature': 0.2467396953084091, 'border_count': 172, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.6205511157155944}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,111] Trial 58 finished with value: 0.9450568845585497 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.022903344954733652, 'l2_leaf_reg': 0.0050895313793075285, 'random_strength': 3.959400177014319e-05, 'bagging_temperature': 7.691139508185991, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.14328631200347425}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,358] Trial 59 finished with value: 0.9449614966901738 and parameters: {'iterations': 288, 'depth': 10, 'learning_rate': 0.052270626553195046, 'l2_leaf_reg': 0.015183999507432818, 'random_strength': 0.0003193911671015348, 'bagging_temperature': 0.7215808592563201, 'border_count': 158, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.5051907715975001}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,626] Trial 60 finished with value: 0.9392610369587242 and parameters: {'iterations': 337, 'depth': 12, 'learning_rate': 0.07355185141560906, 'l2_leaf_reg': 0.20196677808219077, 'random_strength': 9.173337953915923e-07, 'bagging_temperature': 1.076397502882221, 'border_count': 139, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.5483613280711558}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,786] Trial 61 finished with value: 0.9450568845585497 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.022503958124257865, 'l2_leaf_reg': 0.0053822010708529785, 'random_strength': 3.6788525900741224e-06, 'bagging_temperature': 8.340087130052538, 'border_count': 110, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.14046713436027425}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,001] Trial 62 finished with value: 0.9450568845585497 and parameters: {'iterations': 458, 'depth': 11, 'learning_rate': 0.01689186112137248, 'l2_leaf_reg': 0.05213905679989868, 'random_strength': 5.761360055878985e-05, 'bagging_temperature': 3.8785298751967336, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 84, 'rsm': 0.21604658939588595}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,151] Trial 63 finished with value: 0.9451013583702761 and parameters: {'iterations': 489, 'depth': 4, 'learning_rate': 0.0109998556655596, 'l2_leaf_reg': 0.0015933889574844828, 'random_strength': 3.7107547701043355e-05, 'bagging_temperature': 0.5750351844280351, 'border_count': 112, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.17440247613480278}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,325] Trial 64 finished with value: 0.9394580121286875 and parameters: {'iterations': 497, 'depth': 4, 'learning_rate': 0.008862185692537406, 'l2_leaf_reg': 0.0001616306852051432, 'random_strength': 0.0001253545848135207, 'bagging_temperature': 0.5809952238061248, 'border_count': 87, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.39211824641718424}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,557] Trial 65 finished with value: 0.9450568845585497 and parameters: {'iterations': 441, 'depth': 4, 'learning_rate': 0.01927073249172679, 'l2_leaf_reg': 0.8886683537672693, 'random_strength': 0.0009200433649419209, 'bagging_temperature': 0.3258586539625712, 'border_count': 147, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 22, 'rsm': 0.25435277879936763}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:53,561] Trial 66 finished with value: 0.9330174904745441 and parameters: {'iterations': 431, 'depth': 8, 'learning_rate': 0.01121881943404954, 'l2_leaf_reg': 0.001891135856776816, 'random_strength': 0.10334570071942178, 'bagging_temperature': 0.3935708768450864, 'border_count': 215, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 90, 'rsm': 0.19210065058904802}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:54,625] Trial 67 finished with value: 0.9450147969608423 and parameters: {'iterations': 484, 'depth': 3, 'learning_rate': 0.00579402157241798, 'l2_leaf_reg': 0.35127082993071396, 'random_strength': 0.010864405142117882, 'bagging_temperature': 0.7519525888035951, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 67, 'rsm': 0.45408506228049234}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:55,591] Trial 68 finished with value: 0.9391606495664544 and parameters: {'iterations': 459, 'depth': 9, 'learning_rate': 0.012411149890886005, 'l2_leaf_reg': 1.6764351896435874e-05, 'random_strength': 1.310790266546465e-07, 'bagging_temperature': 0.45145858949881645, 'border_count': 55, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 46, 'rsm': 0.3014763801342136}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,469] Trial 69 finished with value: 0.9369181533853135 and parameters: {'iterations': 418, 'depth': 6, 'learning_rate': 0.008387464067222912, 'l2_leaf_reg': 0.08155285274527148, 'random_strength': 0.002509110127115399, 'bagging_temperature': 0.9268562138535151, 'border_count': 71, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.6003005382283918}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,572] Trial 70 finished with value: 0.9390625201399484 and parameters: {'iterations': 309, 'depth': 1, 'learning_rate': 0.03329871150014482, 'l2_leaf_reg': 2.2276605358743353, 'random_strength': 4.9898598389615e-06, 'bagging_temperature': 0.6419929476777696, 'border_count': 106, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 100, 'rsm': 0.49360370831141787}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,743] Trial 71 finished with value: 0.9392165631469979 and parameters: {'iterations': 471, 'depth': 10, 'learning_rate': 0.0252888738684369, 'l2_leaf_reg': 0.005017507709629204, 'random_strength': 2.440068851809699e-05, 'bagging_temperature': 6.3294777334946986, 'border_count': 114, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.14864350704014634}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,916] Trial 72 finished with value: 0.9420281633568404 and parameters: {'iterations': 488, 'depth': 12, 'learning_rate': 0.01827112156919407, 'l2_leaf_reg': 0.0014745826355574527, 'random_strength': 3.275792525199124e-05, 'bagging_temperature': 1.276778289508142, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.15087933871697753}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:57,089] Trial 73 finished with value: 0.9420281633568404 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.042064077989929866, 'l2_leaf_reg': 0.0074787463668816384, 'random_strength': 1.2921631502648065e-05, 'bagging_temperature': 6.807420909116351, 'border_count': 135, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 90, 'rsm': 0.11210268157392836}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:57,572] Trial 74 finished with value: 0.9392165631469979 and parameters: {'iterations': 453, 'depth': 13, 'learning_rate': 0.014324211383182505, 'l2_leaf_reg': 0.01112135218539427, 'random_strength': 4.1357270748163564e-05, 'bagging_temperature': 4.490330592421232, 'border_count': 242, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 39, 'rsm': 0.20919152340585995}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:57,991] Trial 75 finished with value: 0.9422897581604335 and parameters: {'iterations': 436, 'depth': 14, 'learning_rate': 0.02827315737020178, 'l2_leaf_reg': 0.03221556524852036, 'random_strength': 0.00011592539358124591, 'bagging_temperature': 0.2803768481383997, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.663939368673399}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:58,177] Trial 76 finished with value: 0.9450568845585497 and parameters: {'iterations': 498, 'depth': 5, 'learning_rate': 0.021987917437276475, 'l2_leaf_reg': 0.00028929465695989555, 'random_strength': 0.0004455219763426272, 'bagging_temperature': 0.5433075891499852, 'border_count': 100, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 86, 'rsm': 0.1814060619681274}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:00,880] Trial 77 finished with value: 0.9330813491825122 and parameters: {'iterations': 396, 'depth': 10, 'learning_rate': 0.01589601631670435, 'l2_leaf_reg': 0.0340153617396941, 'random_strength': 0.00022120378185857412, 'bagging_temperature': 0.8333005477979103, 'border_count': 108, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 79, 'rsm': 0.2740591686694898}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,054] Trial 78 finished with value: 0.9362630839917611 and parameters: {'iterations': 486, 'depth': 12, 'learning_rate': 0.01250814432155388, 'l2_leaf_reg': 0.08597019771125995, 'random_strength': 3.875658497816237, 'bagging_temperature': 2.027781613667445, 'border_count': 228, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.554428285548262}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,477] Trial 79 finished with value: 0.9332999610216076 and parameters: {'iterations': 470, 'depth': 13, 'learning_rate': 0.03479471943998336, 'l2_leaf_reg': 0.0011038001978353085, 'random_strength': 1.4623871246898063e-06, 'bagging_temperature': 8.298637491032066, 'border_count': 86, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 1, 'rsm': 0.10575314391531795}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,578] Trial 80 finished with value: 0.930715608357473 and parameters: {'iterations': 64, 'depth': 11, 'learning_rate': 0.009970381997329417, 'l2_leaf_reg': 0.002457657979958449, 'random_strength': 5.006664611985971e-07, 'bagging_temperature': 0.3480378302514736, 'border_count': 195, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 83, 'rsm': 0.35085888320037617}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,759] Trial 81 finished with value: 0.939247210975888 and parameters: {'iterations': 474, 'depth': 11, 'learning_rate': 0.023021073395322878, 'l2_leaf_reg': 0.00501303583428343, 'random_strength': 3.297609176261554e-06, 'bagging_temperature': 9.116387247059526, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.1602471439901559}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,945] Trial 82 finished with value: 0.9422759321775974 and parameters: {'iterations': 455, 'depth': 11, 'learning_rate': 0.021341812343129634, 'l2_leaf_reg': 0.0032786030922662217, 'random_strength': 5.6167075068437285e-06, 'bagging_temperature': 7.001846826723126, 'border_count': 93, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.23565806187990584}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,131] Trial 83 finished with value: 0.9450568845585497 and parameters: {'iterations': 486, 'depth': 9, 'learning_rate': 0.025481031559351847, 'l2_leaf_reg': 0.00044861252069219073, 'random_strength': 1.3602639637159673e-05, 'bagging_temperature': 5.269525570746078, 'border_count': 210, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.12292909475376332}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,339] Trial 84 finished with value: 0.9421893707681634 and parameters: {'iterations': 467, 'depth': 10, 'learning_rate': 0.017194280312834556, 'l2_leaf_reg': 0.007334290737691393, 'random_strength': 2.3345258144382588e-06, 'bagging_temperature': 7.5185445722122735, 'border_count': 128, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 57, 'rsm': 0.14168837872160733}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,649] Trial 85 finished with value: 0.9391606495664544 and parameters: {'iterations': 436, 'depth': 10, 'learning_rate': 0.06135057142926861, 'l2_leaf_reg': 0.015040042311610397, 'random_strength': 3.579764468234165e-05, 'bagging_temperature': 9.828877956015381, 'border_count': 121, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 51, 'rsm': 0.3120321567349598}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,749] Trial 86 finished with value: 0.9334278799514462 and parameters: {'iterations': 255, 'depth': 2, 'learning_rate': 0.010786695590314385, 'l2_leaf_reg': 0.24367622394113866, 'random_strength': 8.993969123072843e-07, 'bagging_temperature': 5.586430695006047, 'border_count': 134, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 93, 'rsm': 0.44661208004691777}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,883] Trial 87 finished with value: 0.9420281633568404 and parameters: {'iterations': 422, 'depth': 12, 'learning_rate': 0.029876299308035606, 'l2_leaf_reg': 0.5101805055124192, 'random_strength': 1.6028254589219494e-05, 'bagging_temperature': 2.347165672173358, 'border_count': 74, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.13709507722446973}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:04,057] Trial 88 finished with value: 0.9420281633568404 and parameters: {'iterations': 500, 'depth': 12, 'learning_rate': 0.04807108394354161, 'l2_leaf_reg': 0.13790292373355792, 'random_strength': 2.632778506093437e-07, 'bagging_temperature': 3.569452748252071, 'border_count': 65, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.17151325317899663}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:04,169] Trial 89 finished with value: 0.9392610369587242 and parameters: {'iterations': 209, 'depth': 11, 'learning_rate': 0.013899379180866756, 'l2_leaf_reg': 1.1783486548788338, 'random_strength': 5.439814781017007e-05, 'bagging_temperature': 0.42528108214495586, 'border_count': 113, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 90, 'rsm': 0.20735459506567905}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:09,781] Trial 90 finished with value: 0.9270999046522576 and parameters: {'iterations': 478, 'depth': 9, 'learning_rate': 0.037845787355695625, 'l2_leaf_reg': 2.6515688541607453e-06, 'random_strength': 0.00010733387818114766, 'bagging_temperature': 0.22473932776660133, 'border_count': 174, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 78, 'rsm': 0.5545889385122719}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:10,910] Trial 91 finished with value: 0.9420281633568404 and parameters: {'iterations': 457, 'depth': 11, 'learning_rate': 0.01687742839839296, 'l2_leaf_reg': 0.058337034137483715, 'random_strength': 6.0975438635664064e-05, 'bagging_temperature': 3.8481206713620297, 'border_count': 121, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 85, 'rsm': 0.23247169942382973}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:11,158] Trial 92 finished with value: 0.942245284348707 and parameters: {'iterations': 445, 'depth': 11, 'learning_rate': 0.020355212143055232, 'l2_leaf_reg': 0.051207521743224876, 'random_strength': 4.4117960211688904e-06, 'bagging_temperature': 4.116640848888592, 'border_count': 126, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 84, 'rsm': 0.21191224274175083}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:12,071] Trial 93 finished with value: 0.9392165631469979 and parameters: {'iterations': 464, 'depth': 10, 'learning_rate': 0.026718910027624717, 'l2_leaf_reg': 0.021701446878278626, 'random_strength': 0.0003112530044111786, 'bagging_temperature': 8.294352455693376, 'border_count': 100, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 64, 'rsm': 0.19123093114228457}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:12,954] Trial 94 finished with value: 0.9420281633568404 and parameters: {'iterations': 489, 'depth': 11, 'learning_rate': 0.014921326317568194, 'l2_leaf_reg': 0.10684023710190069, 'random_strength': 0.00015629124932698926, 'bagging_temperature': 1.5913711380912872, 'border_count': 108, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.12680316028591293}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,154] Trial 95 finished with value: 0.9422897581604335 and parameters: {'iterations': 366, 'depth': 15, 'learning_rate': 0.007724090791156113, 'l2_leaf_reg': 4.970487705297225, 'random_strength': 4.832812376313844e-05, 'bagging_temperature': 2.996806980720935, 'border_count': 118, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 91, 'rsm': 0.25001746171887856}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,408] Trial 96 finished with value: 0.9478629958899154 and parameters: {'iterations': 454, 'depth': 13, 'learning_rate': 0.03206259992239698, 'l2_leaf_reg': 9.747885664977631e-07, 'random_strength': 0.0007036688892877016, 'bagging_temperature': 0.676762062406568, 'border_count': 141, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.2828976991951257}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,567] Trial 97 finished with value: 0.944516944120737 and parameters: {'iterations': 431, 'depth': 14, 'learning_rate': 0.03596250183653654, 'l2_leaf_reg': 2.6049742839678903e-08, 'random_strength': 0.0008507615097739611, 'bagging_temperature': 0.6858858531994815, 'border_count': 43, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.2866478375723365}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,860] Trial 98 finished with value: 0.9420281633568404 and parameters: {'iterations': 407, 'depth': 13, 'learning_rate': 0.032590080256233785, 'l2_leaf_reg': 5.3306992270388546e-06, 'random_strength': 0.022674287404467704, 'bagging_temperature': 0.6170819475854629, 'border_count': 166, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.5047854521017533}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:15,792] Trial 99 finished with value: 0.948099087498995 and parameters: {'iterations': 478, 'depth': 12, 'learning_rate': 0.04254101358886379, 'l2_leaf_reg': 1.7277473564532868e-07, 'random_strength': 0.0019440779833289569, 'bagging_temperature': 0.5084286556246295, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 7, 'rsm': 0.37971137763889}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:17,725] Trial 100 finished with value: 0.9421995038264234 and parameters: {'iterations': 447, 'depth': 13, 'learning_rate': 0.054553627666991615, 'l2_leaf_reg': 1.9031563366687202e-07, 'random_strength': 0.001478569010347561, 'bagging_temperature': 0.5020127547283775, 'border_count': 180, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 8, 'rsm': 0.3985919741588475}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:18,099] Trial 101 finished with value: 0.938893699917104 and parameters: {'iterations': 473, 'depth': 12, 'learning_rate': 0.04289147265365806, 'l2_leaf_reg': 7.177530776956312e-08, 'random_strength': 0.005112570354371122, 'bagging_temperature': 0.8041822809136442, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 67, 'rsm': 0.3425524641203796}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:18,829] Trial 102 finished with value: 0.933263873412859 and parameters: {'iterations': 491, 'depth': 12, 'learning_rate': 0.02226381223292443, 'l2_leaf_reg': 9.120516127702251e-07, 'random_strength': 0.0025444221342604914, 'bagging_temperature': 0.564255198899972, 'border_count': 142, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 19, 'rsm': 0.31732954534178587}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:19,365] Trial 103 finished with value: 0.9363490493566118 and parameters: {'iterations': 481, 'depth': 13, 'learning_rate': 0.02483206298542291, 'l2_leaf_reg': 1.5137385022985336e-08, 'random_strength': 0.0007757331181904254, 'bagging_temperature': 0.45248966491294457, 'border_count': 134, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 34, 'rsm': 0.38005525681900953}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:19,840] Trial 104 finished with value: 0.9449682921457203 and parameters: {'iterations': 460, 'depth': 12, 'learning_rate': 0.018505965152376395, 'l2_leaf_reg': 1.5186867963902818e-06, 'random_strength': 0.0015299099277733435, 'bagging_temperature': 0.9604435343858411, 'border_count': 151, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 59, 'rsm': 0.48182633166282013}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:20,085] Trial 105 finished with value: 0.9420419893396765 and parameters: {'iterations': 467, 'depth': 14, 'learning_rate': 0.02999292909768791, 'l2_leaf_reg': 1.0164054698257947e-07, 'random_strength': 0.009267200470185082, 'bagging_temperature': 0.3598497578581198, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.41010965813067535}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:20,351] Trial 106 finished with value: 0.9478823107512284 and parameters: {'iterations': 414, 'depth': 13, 'learning_rate': 0.07309614882931127, 'l2_leaf_reg': 0.0008543057718065979, 'random_strength': 0.0002524560160550367, 'bagging_temperature': 0.4071297784570186, 'border_count': 162, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.266369881554506}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:20,608] Trial 107 finished with value: 0.936463886811552 and parameters: {'iterations': 440, 'depth': 13, 'learning_rate': 0.08190444773381277, 'l2_leaf_reg': 3.214319388206344e-07, 'random_strength': 0.0002612129001674984, 'bagging_temperature': 0.3890984495007036, 'border_count': 147, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 75, 'rsm': 0.270903538495802}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:21,136] Trial 108 finished with value: 0.9308553916078927 and parameters: {'iterations': 416, 'depth': 15, 'learning_rate': 0.10695383481205312, 'l2_leaf_reg': 0.0008919146734425161, 'random_strength': 0.0006207710545904959, 'bagging_temperature': 0.317566864479746, 'border_count': 160, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 70, 'rsm': 0.538778533244966}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:21,430] Trial 109 finished with value: 0.9420281633568404 and parameters: {'iterations': 427, 'depth': 14, 'learning_rate': 0.1469107367152301, 'l2_leaf_reg': 4.444931506830675e-05, 'random_strength': 0.4306633649575429, 'bagging_temperature': 0.535895207806519, 'border_count': 139, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.28942940342239365}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:47,562] Trial 110 finished with value: 0.9141406149187812 and parameters: {'iterations': 393, 'depth': 12, 'learning_rate': 0.0701156386030421, 'l2_leaf_reg': 1.0446575978813497e-08, 'random_strength': 0.003101478071164495, 'bagging_temperature': 0.4225179746298636, 'border_count': 191, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 77, 'rsm': 0.5676355322007246}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:49,102] Trial 111 finished with value: 0.9392980046266818 and parameters: {'iterations': 452, 'depth': 11, 'learning_rate': 0.04157548503684166, 'l2_leaf_reg': 9.034305302437844e-05, 'random_strength': 0.0004057322184259633, 'bagging_temperature': 0.6827176480053725, 'border_count': 167, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 63, 'rsm': 0.3691644950908456}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:50,073] Trial 112 finished with value: 0.9333191418502012 and parameters: {'iterations': 494, 'depth': 12, 'learning_rate': 0.05012391268407289, 'l2_leaf_reg': 2.2291361780007068e-08, 'random_strength': 8.462194507039125e-05, 'bagging_temperature': 0.4730541412136414, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 66, 'rsm': 0.24758489842870557}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:51,388] Trial 113 finished with value: 0.9365108528125179 and parameters: {'iterations': 479, 'depth': 10, 'learning_rate': 0.012897399835445968, 'l2_leaf_reg': 0.0004444637160149302, 'random_strength': 2.21707333469302e-05, 'bagging_temperature': 0.5854775168313623, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 29, 'rsm': 0.6010628227303336}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:52,318] Trial 114 finished with value: 0.9423468716502944 and parameters: {'iterations': 470, 'depth': 13, 'learning_rate': 0.061018518512915516, 'l2_leaf_reg': 0.0015083083238610587, 'random_strength': 0.00015939256236599907, 'bagging_temperature': 0.497044168127894, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.5157982122697622}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:52,675] Trial 115 finished with value: 0.9449308488612835 and parameters: {'iterations': 453, 'depth': 14, 'learning_rate': 0.019576894417447522, 'l2_leaf_reg': 0.00017465568855511566, 'random_strength': 1.0722231591328903e-05, 'bagging_temperature': 0.7402991352316811, 'border_count': 156, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 82, 'rsm': 0.4158043971131127}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:52,876] Trial 116 finished with value: 0.9420281633568404 and parameters: {'iterations': 482, 'depth': 11, 'learning_rate': 0.023401534386045135, 'l2_leaf_reg': 0.0041277449321686505, 'random_strength': 0.16395534032321624, 'bagging_temperature': 0.39074084924312, 'border_count': 229, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 99, 'rsm': 0.16361722425973954}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,110] Trial 117 finished with value: 0.9450568845585497 and parameters: {'iterations': 439, 'depth': 12, 'learning_rate': 0.03149277628843053, 'l2_leaf_reg': 0.01123676927285539, 'random_strength': 6.393237174912083e-06, 'bagging_temperature': 0.650201692371258, 'border_count': 138, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.18485433503209892}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,368] Trial 118 finished with value: 0.9364356107660455 and parameters: {'iterations': 500, 'depth': 13, 'learning_rate': 0.03673691330874392, 'l2_leaf_reg': 0.2799205983076537, 'random_strength': 0.0016616549946443778, 'bagging_temperature': 1.1434304755513767, 'border_count': 93, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 92, 'rsm': 0.303980336947833}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,563] Trial 119 finished with value: 0.9360683747634487 and parameters: {'iterations': 355, 'depth': 10, 'learning_rate': 0.026192218124677005, 'l2_leaf_reg': 5.2505961187717196e-08, 'random_strength': 0.04057701767400652, 'bagging_temperature': 0.28706061899925556, 'border_count': 32, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 42, 'rsm': 0.4499415775570732}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,752] Trial 120 finished with value: 0.9420281633568404 and parameters: {'iterations': 373, 'depth': 5, 'learning_rate': 0.04446704544563856, 'l2_leaf_reg': 0.4538460139184795, 'random_strength': 3.1111899899088475e-05, 'bagging_temperature': 0.2425486475025021, 'border_count': 246, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.22838517640724643}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,959] Trial 121 finished with value: 0.9394135383169611 and parameters: {'iterations': 460, 'depth': 11, 'learning_rate': 0.017012275631636556, 'l2_leaf_reg': 2.0171376606739177e-07, 'random_strength': 8.792564636872177e-05, 'bagging_temperature': 2.5981546478630135, 'border_count': 122, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.22013559649923678}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,218] Trial 122 finished with value: 0.9450568845585497 and parameters: {'iterations': 467, 'depth': 11, 'learning_rate': 0.015246093022030375, 'l2_leaf_reg': 0.19032853338636235, 'random_strength': 1.9249302192365374e-06, 'bagging_temperature': 4.7543569468289455, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.2654905501049236}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,412] Trial 123 finished with value: 0.9422759321775974 and parameters: {'iterations': 488, 'depth': 12, 'learning_rate': 0.011621123531896068, 'l2_leaf_reg': 0.037647845056465574, 'random_strength': 5.901004171329165e-05, 'bagging_temperature': 6.224125963475733, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 87, 'rsm': 0.17393984193004308}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,708] Trial 124 finished with value: 0.9392165631469979 and parameters: {'iterations': 452, 'depth': 10, 'learning_rate': 0.020963152184374403, 'l2_leaf_reg': 0.0006243147662467919, 'random_strength': 0.0002131427399944794, 'bagging_temperature': 7.743944404779233, 'border_count': 220, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.32484174711862224}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,964] Trial 125 finished with value: 0.9366325859360087 and parameters: {'iterations': 476, 'depth': 11, 'learning_rate': 0.010412369273060383, 'l2_leaf_reg': 0.00628453086497708, 'random_strength': 1.0694728932114263e-06, 'bagging_temperature': 0.5377842172748432, 'border_count': 208, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 85, 'rsm': 0.20046815277795216}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:55,238] Trial 126 finished with value: 0.9479394242410895 and parameters: {'iterations': 459, 'depth': 12, 'learning_rate': 0.027921560248912368, 'l2_leaf_reg': 0.0011197201303974583, 'random_strength': 3.7150832167032144e-05, 'bagging_temperature': 0.33772312759685646, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.27829439379604715}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:55,459] Trial 127 finished with value: 0.9478823107512284 and parameters: {'iterations': 416, 'depth': 12, 'learning_rate': 0.02695493912678957, 'l2_leaf_reg': 0.000363754132668095, 'random_strength': 1.6953469751716863e-05, 'bagging_temperature': 0.42078596928585504, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.33967599922122954}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:55,763] Trial 128 finished with value: 0.9420991028295376 and parameters: {'iterations': 414, 'depth': 13, 'learning_rate': 0.030581915215354923, 'l2_leaf_reg': 1.9892774757125386e-05, 'random_strength': 1.9636675912559615e-05, 'bagging_temperature': 0.3441681809788324, 'border_count': 135, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.3535543107245493}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:56,117] Trial 129 finished with value: 0.9393918946301925 and parameters: {'iterations': 432, 'depth': 12, 'learning_rate': 0.028629067859029782, 'l2_leaf_reg': 0.00029759590926787367, 'random_strength': 3.816540308358045e-05, 'bagging_temperature': 0.4304419133130016, 'border_count': 131, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 39, 'rsm': 0.2823066601473922}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:56,471] Trial 130 finished with value: 0.9448319458627505 and parameters: {'iterations': 425, 'depth': 12, 'learning_rate': 0.035334699668356964, 'l2_leaf_reg': 0.002309612414548722, 'random_strength': 9.50603405581896e-06, 'bagging_temperature': 0.1921181189333905, 'border_count': 150, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 55, 'rsm': 0.3421712325642315}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:56,716] Trial 131 finished with value: 0.9365180744718671 and parameters: {'iterations': 463, 'depth': 13, 'learning_rate': 0.2502100961097631, 'l2_leaf_reg': 0.0009007701989759662, 'random_strength': 2.773833098122904e-05, 'bagging_temperature': 0.31330238318056797, 'border_count': 114, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.31829183987372855}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,324] Trial 132 finished with value: 0.9136990147276919 and parameters: {'iterations': 442, 'depth': 11, 'learning_rate': 0.024348095854665255, 'l2_leaf_reg': 0.001264909323666646, 'random_strength': 3.150676241429889e-06, 'bagging_temperature': 0.46186652674322926, 'border_count': 143, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 72, 'rsm': 0.8682699354405292}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,517] Trial 133 finished with value: 0.9421995038264234 and parameters: {'iterations': 401, 'depth': 12, 'learning_rate': 0.019311103012232354, 'l2_leaf_reg': 0.0019184237342172986, 'random_strength': 0.00010217748102388497, 'bagging_temperature': 0.3695318985236949, 'border_count': 97, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.30183511209079117}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,730] Trial 134 finished with value: 0.9423051115089043 and parameters: {'iterations': 489, 'depth': 12, 'learning_rate': 0.02774464488294973, 'l2_leaf_reg': 0.00040945750063480554, 'random_strength': 1.576337834706906e-05, 'bagging_temperature': 0.5123293943299259, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.25543055128232267}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,893] Trial 135 finished with value: 0.9391606495664544 and parameters: {'iterations': 475, 'depth': 13, 'learning_rate': 0.02363710203132887, 'l2_leaf_reg': 5.247097796502152e-07, 'random_strength': 1.0426043429706933e-05, 'bagging_temperature': 0.6091999487797312, 'border_count': 127, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 78, 'rsm': 0.10114604580153895}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,115] Trial 136 finished with value: 0.9450707105413858 and parameters: {'iterations': 387, 'depth': 11, 'learning_rate': 0.05275588992091221, 'l2_leaf_reg': 8.421747261566226e-05, 'random_strength': 0.000141431813427501, 'bagging_temperature': 0.40818391430649775, 'border_count': 109, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.5305909051010704}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,254] Trial 137 finished with value: 0.9422681144736649 and parameters: {'iterations': 388, 'depth': 2, 'learning_rate': 0.054322930763598634, 'l2_leaf_reg': 0.0001949978469938516, 'random_strength': 0.0004333104292700143, 'bagging_temperature': 0.2731806983293307, 'border_count': 103, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 100, 'rsm': 0.498687781787593}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,643] Trial 138 finished with value: 0.9390825456894836 and parameters: {'iterations': 347, 'depth': 11, 'learning_rate': 0.040161823283521164, 'l2_leaf_reg': 0.0006602824581046081, 'random_strength': 0.00017097152095899896, 'bagging_temperature': 0.41607380714001674, 'border_count': 136, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 49, 'rsm': 0.5270340614503363}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,926] Trial 139 finished with value: 0.9337256816021439 and parameters: {'iterations': 401, 'depth': 14, 'learning_rate': 0.06628587940533412, 'l2_leaf_reg': 1.153850186992474e-05, 'random_strength': 1.0189969346701975e-07, 'bagging_temperature': 0.8727787081175186, 'border_count': 131, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.5621517728185998}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:59,487] Trial 140 finished with value: 0.9309817335506512 and parameters: {'iterations': 447, 'depth': 12, 'learning_rate': 0.04873334111963402, 'l2_leaf_reg': 0.9943938630341599, 'random_strength': 0.016694319781494524, 'bagging_temperature': 0.3512913463453787, 'border_count': 60, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 12, 'rsm': 0.47806253504933655}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:59,771] Trial 141 finished with value: 0.9449308488612835 and parameters: {'iterations': 410, 'depth': 11, 'learning_rate': 0.09080696553566514, 'l2_leaf_reg': 9.823038775267924e-05, 'random_strength': 6.939854564405356e-05, 'bagging_temperature': 0.4616531938747425, 'border_count': 108, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.6087092617769291}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,004] Trial 142 finished with value: 0.9392165631469979 and parameters: {'iterations': 383, 'depth': 11, 'learning_rate': 0.03210113857890355, 'l2_leaf_reg': 0.0026887421482416993, 'random_strength': 3.765884321811762e-05, 'bagging_temperature': 0.4118834611950506, 'border_count': 115, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 24, 'rsm': 0.13535857801156687}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,287] Trial 143 finished with value: 0.9420419893396765 and parameters: {'iterations': 432, 'depth': 10, 'learning_rate': 0.038798992992227554, 'l2_leaf_reg': 0.0034741180567567412, 'random_strength': 0.0002713146202368732, 'bagging_temperature': 1.8012944200478604, 'border_count': 110, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.5400120064708985}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,628] Trial 144 finished with value: 0.942245284348707 and parameters: {'iterations': 418, 'depth': 11, 'learning_rate': 0.0791067496320934, 'l2_leaf_reg': 2.0789296632826364, 'random_strength': 0.00012954682210043842, 'bagging_temperature': 0.29682505882415755, 'border_count': 124, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.46616896879851744}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,977] Trial 145 finished with value: 0.9307339647298944 and parameters: {'iterations': 456, 'depth': 12, 'learning_rate': 0.057708055393875246, 'l2_leaf_reg': 1.344858568035081e-06, 'random_strength': 4.540543632281483e-06, 'bagging_temperature': 0.5584292910538805, 'border_count': 101, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 90, 'rsm': 0.6415174624180923}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:01,154] Trial 146 finished with value: 0.9391606495664544 and parameters: {'iterations': 483, 'depth': 10, 'learning_rate': 0.044217578258479565, 'l2_leaf_reg': 0.0011889679366554329, 'random_strength': 1.464865467543225, 'bagging_temperature': 0.32672860462852166, 'border_count': 83, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.26647106843219254}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:01,475] Trial 147 finished with value: 0.9364356107660455 and parameters: {'iterations': 468, 'depth': 12, 'learning_rate': 0.021464305942117096, 'l2_leaf_reg': 0.009334993746607368, 'random_strength': 0.000668552265044122, 'bagging_temperature': 8.862006303293871, 'border_count': 116, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.5154318707930476}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:01,820] Trial 148 finished with value: 0.942245284348707 and parameters: {'iterations': 494, 'depth': 13, 'learning_rate': 0.013240135648172328, 'l2_leaf_reg': 9.256222542785185e-08, 'random_strength': 0.004389309226115299, 'bagging_temperature': 0.3810188561669928, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 68, 'rsm': 0.2905578012712258}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:02,182] Trial 149 finished with value: 0.9420419893396765 and parameters: {'iterations': 442, 'depth': 12, 'learning_rate': 0.026276610480490587, 'l2_leaf_reg': 0.018184055160189394, 'random_strength': 0.001160278323404396, 'bagging_temperature': 0.4994469700760825, 'border_count': 129, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 92, 'rsm': 0.5892674146326472}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:02,932] Trial 150 finished with value: 0.9393576247364175 and parameters: {'iterations': 479, 'depth': 11, 'learning_rate': 0.017909665495729164, 'l2_leaf_reg': 3.418791190835952e-08, 'random_strength': 4.9316581417474394e-05, 'bagging_temperature': 0.2581840409523552, 'border_count': 105, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 6, 'rsm': 0.33059365320417256}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,120] Trial 151 finished with value: 0.9392165631469979 and parameters: {'iterations': 460, 'depth': 11, 'learning_rate': 0.015844361923020113, 'l2_leaf_reg': 0.06242436487813967, 'random_strength': 2.7294282776467616e-05, 'bagging_temperature': 2.237567853852061, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.15432115118896458}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,275] Trial 152 finished with value: 0.9420281633568404 and parameters: {'iterations': 307, 'depth': 10, 'learning_rate': 0.03513004502618466, 'l2_leaf_reg': 0.10677773168166566, 'random_strength': 7.12467611021974e-05, 'bagging_temperature': 3.4000812647715395, 'border_count': 123, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 83, 'rsm': 0.21908078522196517}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,556] Trial 153 finished with value: 0.9422897581604335 and parameters: {'iterations': 454, 'depth': 11, 'learning_rate': 0.01736942289114766, 'l2_leaf_reg': 0.6057033139880593, 'random_strength': 1.662852062105787e-05, 'bagging_temperature': 5.1533816618993225, 'border_count': 240, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.2500286572700599}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,804] Trial 154 finished with value: 0.9392165631469979 and parameters: {'iterations': 470, 'depth': 11, 'learning_rate': 0.02180369139093789, 'l2_leaf_reg': 5.365532742813126e-06, 'random_strength': 4.764746563966035e-05, 'bagging_temperature': 6.962252063321166, 'border_count': 250, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.24164552701504163}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,055] Trial 155 finished with value: 0.9420281633568404 and parameters: {'iterations': 437, 'depth': 12, 'learning_rate': 0.014025048100410055, 'l2_leaf_reg': 0.02942261064762721, 'random_strength': 0.00012661997678511193, 'bagging_temperature': 1.428644549746044, 'border_count': 143, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 61, 'rsm': 0.19733653394586823}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,343] Trial 156 finished with value: 0.9424733829640397 and parameters: {'iterations': 424, 'depth': 15, 'learning_rate': 0.027584687851370693, 'l2_leaf_reg': 0.29289799744567774, 'random_strength': 0.00029810253532579494, 'bagging_temperature': 0.5910808047715936, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 89, 'rsm': 0.3649935157963945}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,567] Trial 157 finished with value: 0.9422897581604335 and parameters: {'iterations': 500, 'depth': 8, 'learning_rate': 0.00901702182872297, 'l2_leaf_reg': 3.225175618190725e-05, 'random_strength': 5.9851862067132196e-06, 'bagging_temperature': 9.908711348745099, 'border_count': 148, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.2299046581579018}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,896] Trial 158 finished with value: 0.9392330734328883 and parameters: {'iterations': 462, 'depth': 13, 'learning_rate': 0.0013935426903720562, 'l2_leaf_reg': 0.14008351382588624, 'random_strength': 2.369260775666672e-05, 'bagging_temperature': 0.4395591771328395, 'border_count': 133, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 74, 'rsm': 0.27863519108727014}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:06,065] Trial 159 finished with value: 0.9301439811851072 and parameters: {'iterations': 155, 'depth': 9, 'learning_rate': 0.019097821061106832, 'l2_leaf_reg': 0.006194130972191863, 'random_strength': 1.4295326838866243e-05, 'bagging_temperature': 0.6814306150232909, 'border_count': 163, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 65, 'rsm': 0.43586584061754363}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:07,160] Trial 160 finished with value: 0.9420218435177732 and parameters: {'iterations': 488, 'depth': 10, 'learning_rate': 0.032756415738802266, 'l2_leaf_reg': 0.0008852235114852314, 'random_strength': 8.600949207782079e-05, 'bagging_temperature': 0.5373270810790087, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 52, 'rsm': 0.4917947838104507}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:07,537] Trial 161 finished with value: 0.9419079718821625 and parameters: {'iterations': 446, 'depth': 4, 'learning_rate': 0.015539514333519456, 'l2_leaf_reg': 4.889776520122877, 'random_strength': 0.0009313366488436875, 'bagging_temperature': 0.3672581246244092, 'border_count': 155, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 2, 'rsm': 0.2673764128336307}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:08,380] Trial 162 finished with value: 0.9448535895495193 and parameters: {'iterations': 475, 'depth': 3, 'learning_rate': 0.021850054135842855, 'l2_leaf_reg': 0.07511660282185649, 'random_strength': 0.0020123581833509357, 'bagging_temperature': 0.344424780392622, 'border_count': 127, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 78, 'rsm': 0.2089112701899995}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,247] Trial 163 finished with value: 0.9450568845585497 and parameters: {'iterations': 320, 'depth': 4, 'learning_rate': 0.025276377314971288, 'l2_leaf_reg': 0.1775039781494037, 'random_strength': 5.901525276899961e-07, 'bagging_temperature': 0.47513410689487956, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 45, 'rsm': 0.3056672204395963}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,396] Trial 164 finished with value: 0.9420281633568404 and parameters: {'iterations': 451, 'depth': 3, 'learning_rate': 0.017027809049485573, 'l2_leaf_reg': 0.8431126650682025, 'random_strength': 0.006265987027362102, 'bagging_temperature': 0.3287967201175384, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.18023769816221066}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,660] Trial 165 finished with value: 0.9391964173250944 and parameters: {'iterations': 441, 'depth': 5, 'learning_rate': 0.019654004388037327, 'l2_leaf_reg': 2.962806671659982, 'random_strength': 0.00046456659205713837, 'bagging_temperature': 0.41793940274356656, 'border_count': 136, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 20, 'rsm': 0.2491760323144459}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,841] Trial 166 finished with value: 0.9420281633568404 and parameters: {'iterations': 431, 'depth': 12, 'learning_rate': 0.04825961750253769, 'l2_leaf_reg': 0.3864623653407632, 'random_strength': 0.0002106851591803803, 'bagging_temperature': 0.30726417093872255, 'border_count': 95, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 76, 'rsm': 0.12462026159271422}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:10,749] Trial 167 finished with value: 0.9364292909269782 and parameters: {'iterations': 464, 'depth': 11, 'learning_rate': 0.028930996110599103, 'l2_leaf_reg': 0.04410691026043362, 'random_strength': 0.0011414873923234618, 'bagging_temperature': 0.3772427474271183, 'border_count': 150, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 25, 'rsm': 0.5470029379168437}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,025] Trial 168 finished with value: 0.9392165631469979 and parameters: {'iterations': 483, 'depth': 7, 'learning_rate': 0.023530434704186497, 'l2_leaf_reg': 0.00043497423339023495, 'random_strength': 3.700167074678586e-05, 'bagging_temperature': 0.6287303886622022, 'border_count': 178, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 82, 'rsm': 0.2872040142291833}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,352] Trial 169 finished with value: 0.9391606495664544 and parameters: {'iterations': 419, 'depth': 11, 'learning_rate': 0.011066677702838626, 'l2_leaf_reg': 3.3218560135089747e-07, 'random_strength': 6.273259312642815e-05, 'bagging_temperature': 0.47382001617043684, 'border_count': 90, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 14, 'rsm': 0.1503567953926859}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,502] Trial 170 finished with value: 0.9420281633568404 and parameters: {'iterations': 410, 'depth': 4, 'learning_rate': 0.06752711692568371, 'l2_leaf_reg': 0.001710704283225401, 'random_strength': 7.762246146156258e-06, 'bagging_temperature': 7.677579394294883, 'border_count': 106, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.22951185589278955}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,668] Trial 171 finished with value: 0.939247210975888 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.02000585732933726, 'l2_leaf_reg': 0.0006763625137768598, 'random_strength': 0.0005407013316711388, 'bagging_temperature': 0.5340715524087578, 'border_count': 101, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.16311940628182714}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,837] Trial 172 finished with value: 0.9420281633568404 and parameters: {'iterations': 492, 'depth': 5, 'learning_rate': 0.014896680959692137, 'l2_leaf_reg': 1.4385889711686615, 'random_strength': 0.0007178660770454293, 'bagging_temperature': 0.7563960208234407, 'border_count': 111, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 86, 'rsm': 0.17243296476590866}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,000] Trial 173 finished with value: 0.9450568845585497 and parameters: {'iterations': 473, 'depth': 5, 'learning_rate': 0.023027426925292, 'l2_leaf_reg': 0.0002781682518945414, 'random_strength': 0.00010782305847558164, 'bagging_temperature': 0.5867396501064782, 'border_count': 99, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 84, 'rsm': 0.19470730255701207}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,235] Trial 174 finished with value: 0.939377770558321 and parameters: {'iterations': 482, 'depth': 4, 'learning_rate': 0.03241964888238338, 'l2_leaf_reg': 0.0003457154290776943, 'random_strength': 0.00044451681264570474, 'bagging_temperature': 0.4432670512593227, 'border_count': 233, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 80, 'rsm': 0.26332909539982013}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,533] Trial 175 finished with value: 0.9394832914849566 and parameters: {'iterations': 457, 'depth': 13, 'learning_rate': 0.04045814491944505, 'l2_leaf_reg': 0.0001402936281707434, 'random_strength': 0.0001840161471214937, 'bagging_temperature': 0.5079765193842785, 'border_count': 213, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 87, 'rsm': 0.3167030107845214}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,760] Trial 176 finished with value: 0.9420281633568404 and parameters: {'iterations': 493, 'depth': 4, 'learning_rate': 0.027519881479168753, 'l2_leaf_reg': 0.004053512628934247, 'random_strength': 0.0003219786489434715, 'bagging_temperature': 0.41135083844257087, 'border_count': 185, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 92, 'rsm': 0.34090137490760997}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,115] Trial 177 finished with value: 0.9478701466895731 and parameters: {'iterations': 294, 'depth': 14, 'learning_rate': 0.017432667951942236, 'l2_leaf_reg': 8.069010518000647e-05, 'random_strength': 0.10401852426690426, 'bagging_temperature': 0.22484682170681464, 'border_count': 203, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 98, 'rsm': 0.5766975974859562}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,395] Trial 178 finished with value: 0.9423087176776352 and parameters: {'iterations': 265, 'depth': 14, 'learning_rate': 0.01247518250258224, 'l2_leaf_reg': 0.0002203658912485584, 'random_strength': 0.1334227737202125, 'bagging_temperature': 0.2670035665869987, 'border_count': 196, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.5318296390483455}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,644] Trial 179 finished with value: 0.9448535895495193 and parameters: {'iterations': 238, 'depth': 14, 'learning_rate': 0.01807673012308473, 'l2_leaf_reg': 0.01399085651991093, 'random_strength': 0.2960932676404893, 'bagging_temperature': 0.15351918050488025, 'border_count': 255, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 96, 'rsm': 0.5114009411786454}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,998] Trial 180 finished with value: 0.9449107030393801 and parameters: {'iterations': 450, 'depth': 14, 'learning_rate': 0.03589837606023441, 'l2_leaf_reg': 6.662649961466868e-05, 'random_strength': 0.07909578018195974, 'bagging_temperature': 0.23722827797048798, 'border_count': 132, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.2793912618414582}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:14,157] Trial 181 finished with value: 0.9422031967509996 and parameters: {'iterations': 282, 'depth': 3, 'learning_rate': 0.020907669083619945, 'l2_leaf_reg': 4.0417023367134544e-05, 'random_strength': 0.0029292950598705124, 'bagging_temperature': 0.2048019984702627, 'border_count': 114, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 98, 'rsm': 0.5726568945580828}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:14,532] Trial 182 finished with value: 0.9308692175907287 and parameters: {'iterations': 300, 'depth': 16, 'learning_rate': 0.016977587931415225, 'l2_leaf_reg': 6.428861894888382e-05, 'random_strength': 4.481525163941594e-05, 'bagging_temperature': 0.2915045702805398, 'border_count': 202, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 94, 'rsm': 0.5886491339618192}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:14,761] Trial 183 finished with value: 0.9394769716458893 and parameters: {'iterations': 221, 'depth': 12, 'learning_rate': 0.024351404002375798, 'l2_leaf_reg': 0.000571971133855846, 'random_strength': 2.4460781047220314e-05, 'bagging_temperature': 0.22238886441296601, 'border_count': 172, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 100, 'rsm': 0.5577041652720683}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:15,345] Trial 184 finished with value: 0.9478606670644598 and parameters: {'iterations': 374, 'depth': 10, 'learning_rate': 0.018862089757160656, 'l2_leaf_reg': 0.0002711773955536017, 'random_strength': 0.00013899680340439353, 'bagging_temperature': 4.376392538372629, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 10, 'rsm': 0.21282910430945437}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:15,933] Trial 185 finished with value: 0.9422251385268036 and parameters: {'iterations': 373, 'depth': 10, 'learning_rate': 0.01341908033642766, 'l2_leaf_reg': 1.3301485751827285e-07, 'random_strength': 8.258702096105676e-05, 'bagging_temperature': 6.313550576053137, 'border_count': 125, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 8, 'rsm': 0.21582168224439763}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:16,955] Trial 186 finished with value: 0.9366461056733522 and parameters: {'iterations': 354, 'depth': 11, 'learning_rate': 0.016015514757403242, 'l2_leaf_reg': 0.0012157604267309754, 'random_strength': 0.00014286883311715454, 'bagging_temperature': 3.8355646079201944, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 4, 'rsm': 0.24455713560531547}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:18,240] Trial 187 finished with value: 0.9393714507192537 and parameters: {'iterations': 387, 'depth': 9, 'learning_rate': 0.029773522710607077, 'l2_leaf_reg': 0.18964502202298492, 'random_strength': 0.05665749832122518, 'bagging_temperature': 4.316804556211732, 'border_count': 224, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 5, 'rsm': 0.29112694915279064}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:19,109] Trial 188 finished with value: 0.9365246787953542 and parameters: {'iterations': 328, 'depth': 10, 'learning_rate': 0.019103470294199343, 'l2_leaf_reg': 6.562015740609845, 'random_strength': 0.030892780955495254, 'bagging_temperature': 5.561691546696606, 'border_count': 129, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 10, 'rsm': 0.6181631034200274}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:20,111] Trial 189 finished with value: 0.9364154649441421 and parameters: {'iterations': 363, 'depth': 12, 'learning_rate': 0.014354312995037964, 'l2_leaf_reg': 0.0881351634444277, 'random_strength': 1.973507344724729e-06, 'bagging_temperature': 8.141642491918113, 'border_count': 137, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 16, 'rsm': 0.19449893094423057}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:49,051] Trial 190 finished with value: 0.9326620320519092 and parameters: {'iterations': 394, 'depth': 13, 'learning_rate': 0.02538912391774518, 'l2_leaf_reg': 0.0024456588938525075, 'random_strength': 0.09893594885717653, 'bagging_temperature': 2.6586561536924234, 'border_count': 119, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 97, 'rsm': 0.4961944560276764}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:50,393] Trial 191 finished with value: 0.9364356107660455 and parameters: {'iterations': 377, 'depth': 15, 'learning_rate': 0.02160748607378081, 'l2_leaf_reg': 0.00018784167765087707, 'random_strength': 5.661101716609462e-05, 'bagging_temperature': 0.5520159277072044, 'border_count': 105, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 33, 'rsm': 0.13638530175267316}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:51,336] Trial 192 finished with value: 0.9365766723554652 and parameters: {'iterations': 345, 'depth': 11, 'learning_rate': 0.018153545563738348, 'l2_leaf_reg': 0.0002689381199903756, 'random_strength': 0.0013202072873539827, 'bagging_temperature': 3.05875393809237, 'border_count': 108, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 47, 'rsm': 0.1833083713837859}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:52,234] Trial 193 finished with value: 0.9422759321775974 and parameters: {'iterations': 472, 'depth': 11, 'learning_rate': 0.01967261015798756, 'l2_leaf_reg': 0.00010269003059595126, 'random_strength': 0.0003224919649464639, 'bagging_temperature': 4.7403514956391515, 'border_count': 114, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.22203325266748072}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:52,590] Trial 194 finished with value: 0.9450707105413858 and parameters: {'iterations': 479, 'depth': 12, 'learning_rate': 0.022953910052071345, 'l2_leaf_reg': 0.00033355714664964474, 'random_strength': 0.00021059453778553297, 'bagging_temperature': 0.3911695421583786, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.53058333271746}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:52,915] Trial 195 finished with value: 0.9479595700629927 and parameters: {'iterations': 468, 'depth': 12, 'learning_rate': 0.027646391674950158, 'l2_leaf_reg': 0.0008940375907121934, 'random_strength': 0.00017370575325460964, 'bagging_temperature': 0.17637761154801543, 'border_count': 123, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 92, 'rsm': 0.5383588788987733}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:53,243] Trial 196 finished with value: 0.9448749352807401 and parameters: {'iterations': 466, 'depth': 12, 'learning_rate': 0.031699768142828835, 'l2_leaf_reg': 0.0010108484321680307, 'random_strength': 0.00015777611403595265, 'bagging_temperature': 0.14876062009712754, 'border_count': 126, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.5254795998656782}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:53,584] Trial 197 finished with value: 0.9334006901311248 and parameters: {'iterations': 482, 'depth': 12, 'learning_rate': 0.026842474376006505, 'l2_leaf_reg': 0.0006848580407660518, 'random_strength': 0.00010498978622202728, 'bagging_temperature': 0.18830195664870608, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 94, 'rsm': 0.5497198397999028}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:53,820] Trial 198 finished with value: 0.9420419893396765 and parameters: {'iterations': 295, 'depth': 12, 'learning_rate': 0.03677738161683119, 'l2_leaf_reg': 0.00036343825894797515, 'random_strength': 0.0002479113992623705, 'bagging_temperature': 0.14005757368990798, 'border_count': 122, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 89, 'rsm': 0.5391037144265599}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:54,203] Trial 199 finished with value: 0.9450707105413858 and parameters: {'iterations': 460, 'depth': 12, 'learning_rate': 0.04545859371569691, 'l2_leaf_reg': 0.0016986307026388967, 'random_strength': 3.772429639477264e-05, 'bagging_temperature': 0.1322329379931608, 'border_count': 128, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 97, 'rsm': 0.5717542930999647}. Best is trial 99 with value: 0.948099087498995.\n" ] }, { @@ -438,18 +1271,18 @@ "output_type": "stream", "text": [ "Best trial:\n", - "F1 Score: 0.731945\n", + "F1 Score: 0.948099\n", "Parameters:\n", - "iterations: 168\n", - "depth: 5\n", - "learning_rate: 0.00889070096045054\n", - "l2_leaf_reg: 3.173038372914875e-05\n", - "random_strength: 0.0004606096176348796\n", - "bagging_temperature: 0.9387985722566684\n", - "border_count: 56\n", + "iterations: 478\n", + "depth: 12\n", + "learning_rate: 0.04254101358886379\n", + "l2_leaf_reg: 1.7277473564532868e-07\n", + "random_strength: 0.0019440779833289569\n", + "bagging_temperature: 0.5084286556246295\n", + "border_count: 140\n", "grow_policy: Depthwise\n", - "min_data_in_leaf: 92\n", - "rsm: 0.7489477360324039\n" + "min_data_in_leaf: 7\n", + "rsm: 0.37971137763889\n" ] } ], @@ -504,11 +1337,351 @@ "for k, v in best_trial.params.items():\n", " print(f\"{k}: {v}\")" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/dj/6m_rn6_56pvb0zb7k0t6bz4r0000gn/T/ipykernel_1127/3819207535.py:8: DeprecationWarning: Use dataset_load() instead of load_dataset(). load_dataset() will be removed in a future version.\n", + " df = kagglehub.load_dataset(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading from https://www.kaggle.com/api/v1/datasets/download/bhavikjikadara/loan-status-prediction?dataset_version_number=1&file_name=loan_data.csv...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 25.7k/25.7k [00:00<00:00, 504kB/s]\n" + ] + }, + { + "data": { + "text/html": [ + "
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Loan_IDGenderMarriedDependentsEducationSelf_EmployedApplicantIncomeCoapplicantIncomeLoanAmountLoan_Amount_TermCredit_HistoryProperty_AreaLoan_Status
0LP001003MaleYes1GraduateNo45831508.0128.0360.01.0RuralN
1LP001005MaleYes0GraduateYes30000.066.0360.01.0UrbanY
2LP001006MaleYes0Not GraduateNo25832358.0120.0360.01.0UrbanY
3LP001008MaleNo0GraduateNo60000.0141.0360.01.0UrbanY
4LP001013MaleYes0Not GraduateNo23331516.095.0360.01.0UrbanY
..........................................
376LP002953MaleYes3+GraduateNo57030.0128.0360.01.0UrbanY
377LP002974MaleYes0GraduateNo32321950.0108.0360.01.0RuralY
378LP002978FemaleNo0GraduateNo29000.071.0360.01.0RuralY
379LP002979MaleYes3+GraduateNo41060.040.0180.01.0RuralY
380LP002990FemaleNo0GraduateYes45830.0133.0360.00.0SemiurbanN
\n", + "

381 rows × 13 columns

\n", + "
" + ], + "text/plain": [ + " Loan_ID Gender Married Dependents Education Self_Employed \\\n", + "0 LP001003 Male Yes 1 Graduate No \n", + "1 LP001005 Male Yes 0 Graduate Yes \n", + "2 LP001006 Male Yes 0 Not Graduate No \n", + "3 LP001008 Male No 0 Graduate No \n", + "4 LP001013 Male Yes 0 Not Graduate No \n", + ".. ... ... ... ... ... ... \n", + "376 LP002953 Male Yes 3+ Graduate No \n", + "377 LP002974 Male Yes 0 Graduate No \n", + "378 LP002978 Female No 0 Graduate No \n", + "379 LP002979 Male Yes 3+ Graduate No \n", + "380 LP002990 Female No 0 Graduate Yes \n", + "\n", + " ApplicantIncome CoapplicantIncome LoanAmount Loan_Amount_Term \\\n", + "0 4583 1508.0 128.0 360.0 \n", + "1 3000 0.0 66.0 360.0 \n", + "2 2583 2358.0 120.0 360.0 \n", + "3 6000 0.0 141.0 360.0 \n", + "4 2333 1516.0 95.0 360.0 \n", + ".. ... ... ... ... \n", + "376 5703 0.0 128.0 360.0 \n", + "377 3232 1950.0 108.0 360.0 \n", + "378 2900 0.0 71.0 360.0 \n", + "379 4106 0.0 40.0 180.0 \n", + "380 4583 0.0 133.0 360.0 \n", + "\n", + " Credit_History Property_Area Loan_Status \n", + "0 1.0 Rural N \n", + "1 1.0 Urban Y \n", + "2 1.0 Urban Y \n", + "3 1.0 Urban Y \n", + "4 1.0 Urban Y \n", + ".. ... ... ... \n", + "376 1.0 Urban Y \n", + "377 1.0 Rural Y \n", + "378 1.0 Rural Y \n", + "379 1.0 Rural Y \n", + "380 0.0 Semiurban N \n", + "\n", + "[381 rows x 13 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import kagglehub\n", + "from kagglehub import KaggleDatasetAdapter\n", + "\n", + "# Set the path to the file you'd like to load\n", + "file_path = \"loan_data.csv\"\n", + "\n", + "# Load the latest version\n", + "df = kagglehub.load_dataset(\n", + " KaggleDatasetAdapter.PANDAS,\n", + " \"\",\n", + " file_path,\n", + ")\n", + "\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting kagglehub\n", + " Downloading kagglehub-0.3.13-py3-none-any.whl.metadata (38 kB)\n", + "Requirement already satisfied: packaging in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (25.0)\n", + "Requirement already satisfied: pyyaml in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (6.0.2)\n", + "Requirement already satisfied: requests in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (2.32.4)\n", + "Requirement already satisfied: tqdm in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (4.67.1)\n", + "Requirement already satisfied: charset_normalizer<4,>=2 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (3.4.2)\n", + "Requirement already satisfied: idna<4,>=2.5 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (3.10)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (2.5.0)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (2025.7.14)\n", + "Downloading kagglehub-0.3.13-py3-none-any.whl (68 kB)\n", + "Installing collected packages: kagglehub\n", + "Successfully installed kagglehub-0.3.13\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "pip install kagglehub" + ] } ], "metadata": { "kernelspec": { - "display_name": ".venv (3.13.5)", + "display_name": ".venv (3.13.9)", "language": "python", "name": "python3" }, @@ -522,7 +1695,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.5" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/requirements.txt b/requirements.txt index c1e6cc8..04b48c9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,3 @@ scikit-learn>=1.2.2 typing-extensions>=4.1.0; python_version < "3.11" +filelock>=3.20.1 \ No newline at end of file diff --git a/src/linearboost/__init__.py b/src/linearboost/__init__.py index 6c2c0a8..004b273 100644 --- a/src/linearboost/__init__.py +++ b/src/linearboost/__init__.py @@ -1,6 +1,9 @@ -__version__ = "0.1.7" +__version__ = "0.1.9" from .linear_boost import LinearBoostClassifier from .sefr import SEFR -__all__ = ["LinearBoostClassifier", "SEFR"] +__all__ = [ + "LinearBoostClassifier", + "SEFR", +] diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 4088de8..709be93 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -891,6 +891,10 @@ def fit(self, X, y, sample_weight=None) -> Self: # Store validation data for checking validation_data = (training_data_val, y_val, sample_weight_val) y = y_train + if y is None: + raise ValueError( + "Target values 'y' must not be None after validation split." + ) else: y_train = y From d84a277fcbcccff7e31e6c1590cbb6e6821155e9 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 1 Mar 2026 21:24:15 +0100 Subject: [PATCH 2/7] E402 added to ignore list --- pyproject.toml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 1006eeb..08a67e6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -68,3 +68,6 @@ atomic = true profile = "black" skip_gitignore = true known_first_party = ["linearboost"] + +[tool.ruff.lint.per-file-ignores] +"**/*.ipynb" = ["E402"] From bdc92a2eb082880241563cf875194eb5397fc008 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sat, 7 Mar 2026 14:48:40 +0100 Subject: [PATCH 3/7] Security update --- pyproject.toml | 3 --- src/linearboost/linear_boost.py | 7 ++----- 2 files changed, 2 insertions(+), 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 08a67e6..1006eeb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -68,6 +68,3 @@ atomic = true profile = "black" skip_gitignore = true known_first_party = ["linearboost"] - -[tool.ruff.lint.per-file-ignores] -"**/*.ipynb" = ["E402"] diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 931c58e..26b1851 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -892,10 +892,7 @@ def fit(self, X, y, sample_weight=None) -> Self: # Store validation data for checking validation_data = (training_data_val, y_val, sample_weight_val) y = y_train - if y is None: - raise ValueError( - "Target values 'y' must not be None after validation split." - ) + assert y is not None else: y_train = y @@ -2153,4 +2150,4 @@ def predict_proba(self, X): return self._gradient_predict_proba(test_data) # For AdaBoost, use parent implementation - return super().predict_proba(X) + return super().predict_proba(X) \ No newline at end of file From c85411c5107a3546ddd21dd6d645562a8cfd4f45 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sat, 7 Mar 2026 14:57:44 +0100 Subject: [PATCH 4/7] Updating Python requirement --- notebooks/demo_linearboost_usage.ipynb | 6 ++---- uv.lock | 2 +- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/notebooks/demo_linearboost_usage.ipynb b/notebooks/demo_linearboost_usage.ipynb index 4d4fefc..8640c9b 100644 --- a/notebooks/demo_linearboost_usage.ipynb +++ b/notebooks/demo_linearboost_usage.ipynb @@ -2,14 +2,12 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import sys\n", - "\n", - "sys.path.append(\"../src\")\n", - "from linearboost.linear_boost import LinearBoostClassifier" + "from linearboost import LinearBoostClassifier" ] }, { diff --git a/uv.lock b/uv.lock index 3bd1908..19df50a 100644 --- a/uv.lock +++ b/uv.lock @@ -1,6 +1,6 @@ version = 1 revision = 3 -requires-python = ">=3.8, <3.14" +requires-python = ">=3.10, <3.14" [[package]] name = "cfgv" From bb8f51fce4e3556bdaeca63785faccabdf1e0647 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sat, 7 Mar 2026 16:06:14 +0100 Subject: [PATCH 5/7] Lint corrected --- notebooks/demo_linearboost_usage.ipynb | 1 - 1 file changed, 1 deletion(-) diff --git a/notebooks/demo_linearboost_usage.ipynb b/notebooks/demo_linearboost_usage.ipynb index 8640c9b..647e3b5 100644 --- a/notebooks/demo_linearboost_usage.ipynb +++ b/notebooks/demo_linearboost_usage.ipynb @@ -6,7 +6,6 @@ "metadata": {}, "outputs": [], "source": [ - "import sys\n", "from linearboost import LinearBoostClassifier" ] }, From 3aacf90cc625c5f06b159e462fcaa616557e0445 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sat, 7 Mar 2026 16:25:49 +0100 Subject: [PATCH 6/7] Lint corrected --- notebooks/demo_linearboost_usage.ipynb | 3327 ++++++++++++------------ 1 file changed, 1663 insertions(+), 1664 deletions(-) diff --git a/notebooks/demo_linearboost_usage.ipynb b/notebooks/demo_linearboost_usage.ipynb index 647e3b5..511e551 100644 --- a/notebooks/demo_linearboost_usage.ipynb +++ b/notebooks/demo_linearboost_usage.ipynb @@ -1,1700 +1,1699 @@ { - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from linearboost import LinearBoostClassifier" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: xgboost in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (3.0.2)\n", - "Requirement already satisfied: lightgbm in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (4.6.0)\n", - "Requirement already satisfied: catboost in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (1.2.8)\n", - "Requirement already satisfied: numpy in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from xgboost) (2.2.6)\n", - "Requirement already satisfied: scipy in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from xgboost) (1.15.3)\n", - "Requirement already satisfied: graphviz in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (0.21)\n", - "Requirement already satisfied: matplotlib in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (3.10.3)\n", - "Requirement already satisfied: pandas>=0.24 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (2.3.1)\n", - "Requirement already satisfied: plotly in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (6.2.0)\n", - "Requirement already satisfied: six in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (1.17.0)\n", - "Requirement already satisfied: python-dateutil>=2.8.2 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from pandas>=0.24->catboost) (2.9.0.post0)\n", - "Requirement already satisfied: pytz>=2020.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from pandas>=0.24->catboost) (2025.2)\n", - "Requirement already satisfied: tzdata>=2022.7 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from pandas>=0.24->catboost) (2025.2)\n", - "Requirement already satisfied: contourpy>=1.0.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (1.3.3)\n", - "Requirement already satisfied: cycler>=0.10 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (0.12.1)\n", - "Requirement already satisfied: fonttools>=4.22.0 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (4.59.0)\n", - "Requirement already satisfied: kiwisolver>=1.3.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (1.4.8)\n", - "Requirement already satisfied: packaging>=20.0 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (25.0)\n", - "Requirement already satisfied: pillow>=8 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (11.3.0)\n", - "Requirement already satisfied: pyparsing>=2.3.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (3.2.3)\n", - "Requirement already satisfied: narwhals>=1.15.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from plotly->catboost) (2.0.0)\n", - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "pip install xgboost lightgbm catboost" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "from ucimlrepo import fetch_ucirepo\n", - "from sklearn.preprocessing import LabelEncoder\n", - "\n", - "# The Huberman's Survival's id on UCI Machine Learning Repository\n", - "dataset_id = 52\n", - "\n", - "dataset = fetch_ucirepo(id=dataset_id)\n", - "\n", - "# data (as pandas dataframes)\n", - "X = dataset.data.features.copy()\n", - "y = dataset.data.targets\n", - "\n", - "label_encoder = LabelEncoder()\n", - "\n", - "y = label_encoder.fit_transform(y.values.ravel())\n", - "import numpy as np\n", - "\n", - "y = np.where(np.isin(y, [2, 3, 4, 5]), 1, y)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([1, 1, 1, ..., 0, 0, 0], shape=(4601,))" + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from linearboost import LinearBoostClassifier" ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "y" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "# Identify categorical columns\n", - "categorical_cols = X.select_dtypes(include=[\"object\"]).columns.tolist()\n", - "\n", - "# Convert categorical columns to 'category' dtype\n", - "for col in categorical_cols:\n", - " X[col] = X[col].astype(\"category\")\n", - "\n", - "# Handle missing values\n", - "# Fill numeric columns with median\n", - "numeric_cols = X.select_dtypes(include=[\"int64\", \"float64\"]).columns.tolist()\n", - "for col in numeric_cols:\n", - " X[col] = X[col].fillna(X[col].median())\n", - "\n", - "# Fill categorical columns with mode\n", - "for col in categorical_cols:\n", - " X[col] = X[col].fillna(X[col].mode()[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "import warnings\n", - "\n", - "warnings.filterwarnings(\"ignore\", message=\".*ignore_implicit_zeros.*\")\n", - "warnings.filterwarnings(\"ignore\", message=\".*n_quantiles.*\")\n", - "warnings.filterwarnings(\"ignore\", category=RuntimeWarning)\n", - "warnings.filterwarnings(\"ignore\", category=FutureWarning)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**LinearBoost results:**" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-19 22:02:02,037] A new study created in memory with name: no-name-82933463-2c1e-432a-893e-8dccaf42a971\n" - ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-19 22:02:02,719] Trial 0 finished with value: 0.6404040390084329 and parameters: {'n_estimators': 98, 'learning_rate': 0.025040969870000332, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.0036506834438673618, 'degree': 5, 'coef0': 0.3301750124911056}. Best is trial 0 with value: 0.6404040390084329.\n", - "[I 2025-08-19 22:02:03,124] Trial 1 finished with value: 0.5345075877473346 and parameters: {'n_estimators': 223, 'learning_rate': 0.7297126647372456, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.8114762985242304, 'degree': 3, 'coef0': 0.427337620015356}. Best is trial 0 with value: 0.6404040390084329.\n", - "[I 2025-08-19 22:02:03,558] Trial 2 finished with value: 0.8435145697001879 and parameters: {'n_estimators': 400, 'learning_rate': 0.11869138844012254, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.005788104394731735}. Best is trial 2 with value: 0.8435145697001879.\n", - "[I 2025-08-19 22:02:03,711] Trial 3 finished with value: 0.8764210138920593 and parameters: {'n_estimators': 31, 'learning_rate': 0.030091383187136795, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 3 with value: 0.8764210138920593.\n", - "[I 2025-08-19 22:02:04,570] Trial 4 finished with value: 0.8185946867313308 and parameters: {'n_estimators': 319, 'learning_rate': 0.024091883364845683, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'linear'}. Best is trial 3 with value: 0.8764210138920593.\n", - "[I 2025-08-19 22:02:04,750] Trial 5 finished with value: 0.9017212906585973 and parameters: {'n_estimators': 87, 'learning_rate': 0.48142547555682524, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.12840098702472594}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:05,166] Trial 6 finished with value: 0.8300528334061669 and parameters: {'n_estimators': 86, 'learning_rate': 0.2164714650817863, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'sigmoid', 'gamma': 0.15920891724378544, 'coef0': 0.7539946866285475}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:07,510] Trial 7 finished with value: 0.6535195434381997 and parameters: {'n_estimators': 470, 'learning_rate': 0.012901892094153418, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'poly', 'gamma': 3.940362684702575, 'degree': 2, 'coef0': 0.4967650580245552}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:07,913] Trial 8 finished with value: 0.7971266517319944 and parameters: {'n_estimators': 452, 'learning_rate': 0.43676541330692303, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.0967500612488954}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:09,322] Trial 9 finished with value: 0.5694014450011219 and parameters: {'n_estimators': 243, 'learning_rate': 0.012286177632393586, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.0026004536254413, 'degree': 4, 'coef0': 0.15054572715819692}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:09,587] Trial 10 finished with value: 0.8819567586691062 and parameters: {'n_estimators': 157, 'learning_rate': 0.2770406446126875, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.05370625210928932}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:09,829] Trial 11 finished with value: 0.8964421634266355 and parameters: {'n_estimators': 147, 'learning_rate': 0.3006331948489542, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.03955509407249669}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:09,971] Trial 12 finished with value: 0.8521240202153993 and parameters: {'n_estimators': 172, 'learning_rate': 0.9988817093993582, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.023490983805136197}. Best is trial 5 with value: 0.9017212906585973.\n", - "[I 2025-08-19 22:02:10,237] Trial 13 finished with value: 0.9263770712127013 and parameters: {'n_estimators': 35, 'learning_rate': 0.10250765731473209, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.6514127677245307}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:10,424] Trial 14 finished with value: 0.7085679744920659 and parameters: {'n_estimators': 21, 'learning_rate': 0.07966081404443828, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'sigmoid', 'gamma': 0.6310102946471119, 'coef0': 0.9639953544051878}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:10,506] Trial 15 finished with value: 0.5418932173176405 and parameters: {'n_estimators': 315, 'learning_rate': 0.08759215611783155, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 8.453910649175267}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:10,948] Trial 16 finished with value: 0.9031163163136877 and parameters: {'n_estimators': 76, 'learning_rate': 0.052469928102373574, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.5675836541180403}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:11,057] Trial 17 finished with value: 0.7550115293636145 and parameters: {'n_estimators': 13, 'learning_rate': 0.044871824661281395, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8086407703773626}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:11,526] Trial 18 finished with value: 0.53092297245577 and parameters: {'n_estimators': 78, 'learning_rate': 0.1330897164081811, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 2.267555816096478, 'coef0': 0.014870765902805116}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:12,002] Trial 19 finished with value: 0.8675858847685067 and parameters: {'n_estimators': 207, 'learning_rate': 0.05154796109273011, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:12,485] Trial 20 finished with value: 0.9088656344540121 and parameters: {'n_estimators': 303, 'learning_rate': 0.16750558381714575, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.29744031601691207}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:12,954] Trial 21 finished with value: 0.9206498285402447 and parameters: {'n_estimators': 299, 'learning_rate': 0.17348345914734523, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.5243817676865739}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:13,447] Trial 22 finished with value: 0.9115464653740457 and parameters: {'n_estimators': 309, 'learning_rate': 0.1966185423007268, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.27828466414571096}. Best is trial 13 with value: 0.9263770712127013.\n", - "[I 2025-08-19 22:02:14,378] Trial 23 finished with value: 0.9462108116357341 and parameters: {'n_estimators': 369, 'learning_rate': 0.16073435877818204, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9847789259555744}. Best is trial 23 with value: 0.9462108116357341.\n", - "[I 2025-08-19 22:02:15,192] Trial 24 finished with value: 0.9461696031015109 and parameters: {'n_estimators': 361, 'learning_rate': 0.07835520681588722, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.0987046014422583}. Best is trial 23 with value: 0.9462108116357341.\n", - "[I 2025-08-19 22:02:16,105] Trial 25 finished with value: 0.9517798886901965 and parameters: {'n_estimators': 375, 'learning_rate': 0.07269841814479387, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.209952371165283}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:16,984] Trial 26 finished with value: 0.9324487995962987 and parameters: {'n_estimators': 379, 'learning_rate': 0.07230657816758931, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4187279689074788}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:18,776] Trial 27 finished with value: -inf and parameters: {'n_estimators': 374, 'learning_rate': 0.038575969507376164, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 4.714383316597883, 'coef0': 0.7803535797752535}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:19,167] Trial 28 finished with value: 0.8709779688748764 and parameters: {'n_estimators': 421, 'learning_rate': 0.0746916847815778, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:21,551] Trial 29 finished with value: 0.7023921951486901 and parameters: {'n_estimators': 498, 'learning_rate': 0.02085363052154944, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 1.759102678934659, 'degree': 2, 'coef0': 0.6913894433614183}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:21,919] Trial 30 finished with value: 0.859909045397919 and parameters: {'n_estimators': 350, 'learning_rate': 0.060559050608611484, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.4952186713052695}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:23,126] Trial 31 finished with value: 0.9218746518721318 and parameters: {'n_estimators': 354, 'learning_rate': 0.1280653186238248, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8616818169187364}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:23,988] Trial 32 finished with value: 0.9296865784287618 and parameters: {'n_estimators': 410, 'learning_rate': 0.07021730970300748, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7746356369809244}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:24,184] Trial 33 finished with value: 0.8116240901405313 and parameters: {'n_estimators': 276, 'learning_rate': 0.10871708293585933, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 9.388110391883588}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:25,695] Trial 34 finished with value: 0.9293560948390669 and parameters: {'n_estimators': 383, 'learning_rate': 0.034156266307402705, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.429084842782736}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:25,856] Trial 35 finished with value: 0.5852644581410708 and parameters: {'n_estimators': 426, 'learning_rate': 0.1511859326143314, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 1.2486026815845557, 'degree': 5, 'coef0': 0.9704353144695104}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:26,306] Trial 36 finished with value: 0.8763231749616842 and parameters: {'n_estimators': 344, 'learning_rate': 0.09526097425921956, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:27,781] Trial 37 finished with value: 0.9018423220481535 and parameters: {'n_estimators': 380, 'learning_rate': 0.019876822774381235, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.724771837650152}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:28,517] Trial 38 finished with value: 0.9202747486761362 and parameters: {'n_estimators': 453, 'learning_rate': 0.06647223380069087, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.1084783848378548}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:28,942] Trial 39 finished with value: 0.8628370095777891 and parameters: {'n_estimators': 273, 'learning_rate': 0.269922262432126, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.0066123931064254555}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:30,565] Trial 40 finished with value: 0.8050021872275455 and parameters: {'n_estimators': 332, 'learning_rate': 0.02933776477103744, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 0.27010729641241976, 'coef0': 0.22133988641045943}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:31,335] Trial 41 finished with value: 0.9268901508585747 and parameters: {'n_estimators': 411, 'learning_rate': 0.061902309242806756, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.8646613129693383}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:32,431] Trial 42 finished with value: 0.9240947416940678 and parameters: {'n_estimators': 398, 'learning_rate': 0.042508608956588166, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.786058859203096}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:32,890] Trial 43 finished with value: 0.8712087231269168 and parameters: {'n_estimators': 441, 'learning_rate': 0.07930266596666663, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.848021414105109}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:33,835] Trial 44 finished with value: 0.8991133617676276 and parameters: {'n_estimators': 365, 'learning_rate': 0.12330246274809091, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.450448896004862}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:34,438] Trial 45 finished with value: 0.6983797615900317 and parameters: {'n_estimators': 482, 'learning_rate': 0.05239332207965422, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 5.714276346847359, 'degree': 3, 'coef0': 0.6186051595258996}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:34,863] Trial 46 finished with value: 0.9293575787426139 and parameters: {'n_estimators': 394, 'learning_rate': 0.22829327401274127, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.9319488463371248}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:35,220] Trial 47 finished with value: 0.8181102705094435 and parameters: {'n_estimators': 439, 'learning_rate': 0.35502195035823503, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:36,664] Trial 48 finished with value: 0.846325632333387 and parameters: {'n_estimators': 469, 'learning_rate': 0.09448870280660304, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.0010087705216177958}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:37,219] Trial 49 finished with value: 0.9378935239732582 and parameters: {'n_estimators': 334, 'learning_rate': 0.07222234799412496, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.4323404856498683}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:37,371] Trial 50 finished with value: 0.932192378562819 and parameters: {'n_estimators': 334, 'learning_rate': 0.675761337925708, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3921347754260098}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:37,533] Trial 51 finished with value: 0.920993572883402 and parameters: {'n_estimators': 331, 'learning_rate': 0.8027321262951309, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.395150239747632}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:37,949] Trial 52 finished with value: 0.9459583919276465 and parameters: {'n_estimators': 283, 'learning_rate': 0.5044135952817085, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.9424173881795572}. Best is trial 25 with value: 0.9517798886901965.\n", - "[I 2025-08-19 22:02:38,333] Trial 53 finished with value: 0.9543374173629988 and parameters: {'n_estimators': 239, 'learning_rate': 0.5595716808885748, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.647241725838371}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:38,436] Trial 54 finished with value: 0.8514265280726686 and parameters: {'n_estimators': 227, 'learning_rate': 0.48409844695819165, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 4.125551830420961}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:38,683] Trial 55 finished with value: 0.8281731307797214 and parameters: {'n_estimators': 193, 'learning_rate': 0.5985975447789242, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.586444926695531}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:38,721] Trial 56 finished with value: -inf and parameters: {'n_estimators': 278, 'learning_rate': 0.3864373743263281, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 9.558029039004188, 'coef0': 0.02372150656881622}. Best is trial 53 with value: 0.9543374173629988.\n" - ] + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: xgboost in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (3.0.2)\n", + "Requirement already satisfied: lightgbm in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (4.6.0)\n", + "Requirement already satisfied: catboost in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (1.2.8)\n", + "Requirement already satisfied: numpy in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from xgboost) (2.2.6)\n", + "Requirement already satisfied: scipy in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from xgboost) (1.15.3)\n", + "Requirement already satisfied: graphviz in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (0.21)\n", + "Requirement already satisfied: matplotlib in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (3.10.3)\n", + "Requirement already satisfied: pandas>=0.24 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (2.3.1)\n", + "Requirement already satisfied: plotly in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (6.2.0)\n", + "Requirement already satisfied: six in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from catboost) (1.17.0)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from pandas>=0.24->catboost) (2.9.0.post0)\n", + "Requirement already satisfied: pytz>=2020.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from pandas>=0.24->catboost) (2025.2)\n", + "Requirement already satisfied: tzdata>=2022.7 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from pandas>=0.24->catboost) (2025.2)\n", + "Requirement already satisfied: contourpy>=1.0.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (1.3.3)\n", + "Requirement already satisfied: cycler>=0.10 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (0.12.1)\n", + "Requirement already satisfied: fonttools>=4.22.0 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (4.59.0)\n", + "Requirement already satisfied: kiwisolver>=1.3.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (1.4.8)\n", + "Requirement already satisfied: packaging>=20.0 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (25.0)\n", + "Requirement already satisfied: pillow>=8 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (11.3.0)\n", + "Requirement already satisfied: pyparsing>=2.3.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from matplotlib->catboost) (3.2.3)\n", + "Requirement already satisfied: narwhals>=1.15.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from plotly->catboost) (2.0.0)\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "pip install xgboost lightgbm catboost" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Trial failed with exception: \n", - "All the 10 fits failed.\n", - "It is very likely that your model is misconfigured.\n", - "You can try to debug the error by setting error_score='raise'.\n", - "\n", - "Below are more details about the failures:\n", - "--------------------------------------------------------------------------------\n", - "10 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/pipeline.py\", line 662, in fit\n", - " self._final_estimator.fit(Xt, y, **last_step_params[\"fit\"])\n", - " ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 628, in fit\n", - " return super().fit(training_data, y, sample_weight)\n", - " ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/ensemble/_weight_boosting.py\", line 167, in fit\n", - " sample_weight, estimator_weight, estimator_error = self._boost(\n", - " ~~~~~~~~~~~^\n", - " iboost, X, y, sample_weight, random_state\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " )\n", - " ^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 702, in _boost\n", - " raise ValueError(\n", - " \"BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\"\n", - " )\n", - "ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\n", - "\n" - ] + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "from ucimlrepo import fetch_ucirepo\n", + "from sklearn.preprocessing import LabelEncoder\n", + "import numpy as np\n", + "\n", + "# The Huberman's Survival's id on UCI Machine Learning Repository\n", + "dataset_id = 52\n", + "\n", + "dataset = fetch_ucirepo(id=dataset_id)\n", + "\n", + "# data (as pandas dataframes)\n", + "X = dataset.data.features.copy()\n", + "y = dataset.data.targets\n", + "\n", + "label_encoder = LabelEncoder()\n", + "\n", + "y = label_encoder.fit_transform(y.values.ravel())\n", + "y = np.where(np.isin(y, [2, 3, 4, 5]), 1, y)" + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-19 22:02:39,055] Trial 57 finished with value: 0.8717863235369474 and parameters: {'n_estimators': 257, 'learning_rate': 0.5013464948241906, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.4424401922925503}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:39,588] Trial 58 finished with value: 0.6882396202694265 and parameters: {'n_estimators': 293, 'learning_rate': 0.31142751907125016, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'poly', 'gamma': 3.613839721994584, 'degree': 4, 'coef0': 0.32280671741188566}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:39,778] Trial 59 finished with value: 0.8819539998922167 and parameters: {'n_estimators': 233, 'learning_rate': 0.6097668080397359, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.08883583450139441}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:40,441] Trial 60 finished with value: 0.9281749115310631 and parameters: {'n_estimators': 204, 'learning_rate': 0.1538995463327668, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.9153016198187663}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:40,637] Trial 61 finished with value: 0.9239378580080395 and parameters: {'n_estimators': 361, 'learning_rate': 0.8920930290523721, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.069795607208937}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:41,236] Trial 62 finished with value: 0.9377972940442809 and parameters: {'n_estimators': 319, 'learning_rate': 0.08221986476116154, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2190944381431885}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:41,517] Trial 63 finished with value: 0.862790627424238 and parameters: {'n_estimators': 317, 'learning_rate': 0.08593415530250405, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.749002498833249}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:42,108] Trial 64 finished with value: 0.9353188132686524 and parameters: {'n_estimators': 257, 'learning_rate': 0.0561150028803941, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7932014212856044}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:42,349] Trial 65 finished with value: 0.8649001790723136 and parameters: {'n_estimators': 297, 'learning_rate': 0.11050826854916225, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:43,076] Trial 66 finished with value: 0.9266398313868034 and parameters: {'n_estimators': 118, 'learning_rate': 0.04607008180795451, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8383575083908024}. Best is trial 53 with value: 0.9543374173629988.\n", - "[I 2025-08-19 22:02:44,106] Trial 67 finished with value: 0.9546503958241553 and parameters: {'n_estimators': 247, 'learning_rate': 0.21347325986729773, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1809425528201563}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:44,846] Trial 68 finished with value: 0.6989186486192198 and parameters: {'n_estimators': 236, 'learning_rate': 0.429627157442039, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 0.012260381856754793, 'coef0': 0.8372686886361344}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:45,094] Trial 69 finished with value: 0.9354147103952727 and parameters: {'n_estimators': 173, 'learning_rate': 0.18642494354170872, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.476492775061456}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:45,787] Trial 70 finished with value: 0.9293575787426139 and parameters: {'n_estimators': 282, 'learning_rate': 0.14066067971814394, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.6966820470759123}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:46,568] Trial 71 finished with value: 0.9544562382246768 and parameters: {'n_estimators': 265, 'learning_rate': 0.22209149104576692, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2304812552325375}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:47,354] Trial 72 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 254, 'learning_rate': 0.2565268037020722, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8661220775520375}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:48,126] Trial 73 finished with value: 0.9546241015332697 and parameters: {'n_estimators': 210, 'learning_rate': 0.2281741451600984, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.936522572088527}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:48,879] Trial 74 finished with value: 0.9517579938498862 and parameters: {'n_estimators': 210, 'learning_rate': 0.2191416530172179, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6401238802616942}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:49,874] Trial 75 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 214, 'learning_rate': 0.22967638326768033, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.635572239547895}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:50,292] Trial 76 finished with value: 0.9283794764556614 and parameters: {'n_estimators': 214, 'learning_rate': 0.23287522337623806, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.3983494805126542}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:51,082] Trial 77 finished with value: 0.6705043315571843 and parameters: {'n_estimators': 188, 'learning_rate': 0.25405001864614346, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 1.592417751058729, 'degree': 5, 'coef0': 0.6291303425648905}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:51,718] Trial 78 finished with value: 0.9489535935383199 and parameters: {'n_estimators': 148, 'learning_rate': 0.20184930543138635, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0930264745806801}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:52,130] Trial 79 finished with value: 0.8530369159459188 and parameters: {'n_estimators': 249, 'learning_rate': 0.3425617353986758, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.18880724810140742}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:52,324] Trial 80 finished with value: 0.8759702338461084 and parameters: {'n_estimators': 214, 'learning_rate': 0.28502977258205575, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:52,948] Trial 81 finished with value: 0.9432049461723968 and parameters: {'n_estimators': 154, 'learning_rate': 0.20123449299861937, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.1197804185074935}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:53,558] Trial 82 finished with value: 0.94320286269291 and parameters: {'n_estimators': 136, 'learning_rate': 0.244190328611221, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.424597717864778}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:54,092] Trial 83 finished with value: 0.9265953575750772 and parameters: {'n_estimators': 173, 'learning_rate': 0.2113131563444056, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.7751432908813656}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:54,385] Trial 84 finished with value: 0.9405676191829102 and parameters: {'n_estimators': 48, 'learning_rate': 0.1769465491916037, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.1317701234902864}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:55,155] Trial 85 finished with value: 0.9461117353464846 and parameters: {'n_estimators': 262, 'learning_rate': 0.3176795630787612, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 1.9190549701508972}. Best is trial 67 with value: 0.9546503958241553.\n", - "[I 2025-08-19 22:02:55,764] Trial 86 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 193, 'learning_rate': 0.26419239924556914, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.768323929854739}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:55,888] Trial 87 finished with value: 0.8515658309121397 and parameters: {'n_estimators': 182, 'learning_rate': 0.2722479790329728, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 8.067883543139013}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:56,452] Trial 88 finished with value: 0.5249054202956112 and parameters: {'n_estimators': 201, 'learning_rate': 0.3660228120243797, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 2.5435597533944367, 'coef0': 0.1625403380559477}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:56,745] Trial 89 finished with value: 0.9353761797823182 and parameters: {'n_estimators': 217, 'learning_rate': 0.14050947729651117, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.082668135626794}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:57,414] Trial 90 finished with value: 0.9461914397690464 and parameters: {'n_estimators': 243, 'learning_rate': 0.40636575903125277, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1374915009572724}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:58,083] Trial 91 finished with value: 0.9433191177151397 and parameters: {'n_estimators': 137, 'learning_rate': 0.2050658999304865, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6514217851524977}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:58,822] Trial 92 finished with value: 0.9432909030357621 and parameters: {'n_estimators': 225, 'learning_rate': 0.2222123184480564, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.331241527111629}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:02:59,426] Trial 93 finished with value: 0.9488798569635867 and parameters: {'n_estimators': 164, 'learning_rate': 0.17279265207727196, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.9933659596849163}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:00,176] Trial 94 finished with value: 0.9461776790778822 and parameters: {'n_estimators': 268, 'learning_rate': 0.31518497467892653, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.201533416805354}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:00,537] Trial 95 finished with value: 0.9350713788373026 and parameters: {'n_estimators': 110, 'learning_rate': 0.2548250311872609, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.602537975876707}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:01,442] Trial 96 finished with value: 0.9428383837566567 and parameters: {'n_estimators': 197, 'learning_rate': 0.16383718909942865, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.74429116577557}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:02,495] Trial 97 finished with value: 0.6941801663418611 and parameters: {'n_estimators': 236, 'learning_rate': 0.19045988916497364, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 0.5507502417499932, 'degree': 3, 'coef0': 0.5212178203250792}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:02,893] Trial 98 finished with value: 0.9372552798787337 and parameters: {'n_estimators': 183, 'learning_rate': 0.2738956005721183, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 1.5112047541146179}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:03,158] Trial 99 finished with value: 0.8305296592545964 and parameters: {'n_estimators': 243, 'learning_rate': 0.22214604361651502, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.034548703205194466}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:03,330] Trial 100 finished with value: 0.8578592756814178 and parameters: {'n_estimators': 211, 'learning_rate': 0.33169917655289977, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:03,885] Trial 101 finished with value: 0.9377234617768158 and parameters: {'n_estimators': 157, 'learning_rate': 0.17626469712395465, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8986221438856852}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:04,576] Trial 102 finished with value: 0.9489822458261082 and parameters: {'n_estimators': 172, 'learning_rate': 0.293264685705061, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0710442197687955}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:05,435] Trial 103 finished with value: 0.8062559026857938 and parameters: {'n_estimators': 144, 'learning_rate': 0.010553067733616528, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.108454484699699}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:06,248] Trial 104 finished with value: 0.9432935743437543 and parameters: {'n_estimators': 226, 'learning_rate': 0.2975390616899621, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.1467167237895284}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:07,093] Trial 105 finished with value: 0.9518286923687628 and parameters: {'n_estimators': 192, 'learning_rate': 0.24331029503500007, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7495618454027402}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:08,068] Trial 106 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 204, 'learning_rate': 0.26097714815919504, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7638013611577343}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:08,885] Trial 107 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 205, 'learning_rate': 0.252142149886663, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6815108553353053}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:09,304] Trial 108 finished with value: 0.899160357207285 and parameters: {'n_estimators': 251, 'learning_rate': 0.5668562989797123, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.9079402572030912}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:09,341] Trial 109 finished with value: -inf and parameters: {'n_estimators': 193, 'learning_rate': 0.37388674256800275, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 6.342042428769567, 'coef0': 0.8508850801893877}. Best is trial 86 with value: 0.9573878203541313.\n" - ] + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, ..., 0, 0, 0], shape=(4601,))" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Trial failed with exception: \n", - "All the 10 fits failed.\n", - "It is very likely that your model is misconfigured.\n", - "You can try to debug the error by setting error_score='raise'.\n", - "\n", - "Below are more details about the failures:\n", - "--------------------------------------------------------------------------------\n", - "10 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/pipeline.py\", line 662, in fit\n", - " self._final_estimator.fit(Xt, y, **last_step_params[\"fit\"])\n", - " ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 628, in fit\n", - " return super().fit(training_data, y, sample_weight)\n", - " ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/ensemble/_weight_boosting.py\", line 167, in fit\n", - " sample_weight, estimator_weight, estimator_error = self._boost(\n", - " ~~~~~~~~~~~^\n", - " iboost, X, y, sample_weight, random_state\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " )\n", - " ^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 702, in _boost\n", - " raise ValueError(\n", - " \"BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\"\n", - " )\n", - "ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\n", - "\n" - ] + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "# Identify categorical columns\n", + "categorical_cols = X.select_dtypes(include=[\"object\"]).columns.tolist()\n", + "\n", + "# Convert categorical columns to 'category' dtype\n", + "for col in categorical_cols:\n", + " X[col] = X[col].astype(\"category\")\n", + "\n", + "# Handle missing values\n", + "# Fill numeric columns with median\n", + "numeric_cols = X.select_dtypes(include=[\"int64\", \"float64\"]).columns.tolist()\n", + "for col in numeric_cols:\n", + " X[col] = X[col].fillna(X[col].median())\n", + "\n", + "# Fill categorical columns with mode\n", + "for col in categorical_cols:\n", + " X[col] = X[col].fillna(X[col].mode()[0])" + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-19 22:03:09,683] Trial 110 finished with value: 0.9354204269132287 and parameters: {'n_estimators': 223, 'learning_rate': 0.11525970851531234, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.42390474054593}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:10,337] Trial 111 finished with value: 0.9432228758248777 and parameters: {'n_estimators': 184, 'learning_rate': 0.2319177796947066, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3285933571091035}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:10,826] Trial 112 finished with value: 0.9547394467306798 and parameters: {'n_estimators': 172, 'learning_rate': 0.45079109156398994, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.2893364126109446}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:11,421] Trial 113 finished with value: 0.9377302419765551 and parameters: {'n_estimators': 235, 'learning_rate': 0.44759844230443413, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7122505150670086}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:11,715] Trial 114 finished with value: 0.9321772059231634 and parameters: {'n_estimators': 202, 'learning_rate': 0.6764856671426681, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9871144590689882}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:12,580] Trial 115 finished with value: 0.9460809161475096 and parameters: {'n_estimators': 222, 'learning_rate': 0.26207999753938394, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1480447330624464}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:13,366] Trial 116 finished with value: 0.9488718056362714 and parameters: {'n_estimators': 163, 'learning_rate': 0.14775843924623255, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.388882471501774}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:13,630] Trial 117 finished with value: 0.9322849692738714 and parameters: {'n_estimators': 268, 'learning_rate': 0.5585942165767696, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6804771721860126}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:13,919] Trial 118 finished with value: 0.6905746692841864 and parameters: {'n_estimators': 243, 'learning_rate': 0.41799875124416175, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 3.3226800570154715, 'degree': 4, 'coef0': 0.3764539706641709}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:14,007] Trial 119 finished with value: 0.5473898159570962 and parameters: {'n_estimators': 213, 'learning_rate': 0.23662858855680907, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 8.081957798626714}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:14,460] Trial 120 finished with value: 0.9404654768430832 and parameters: {'n_estimators': 178, 'learning_rate': 0.19303072025137125, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.7206005729161484}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:15,334] Trial 121 finished with value: 0.9433827529207601 and parameters: {'n_estimators': 195, 'learning_rate': 0.27516173815741723, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.092849002219574}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:15,773] Trial 122 finished with value: 0.9433011880626585 and parameters: {'n_estimators': 169, 'learning_rate': 0.28751301328977386, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.2666489829518957}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:16,350] Trial 123 finished with value: 0.9489562648463121 and parameters: {'n_estimators': 206, 'learning_rate': 0.34002413096362905, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.791063939373234}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:17,309] Trial 124 finished with value: 0.948832689197155 and parameters: {'n_estimators': 231, 'learning_rate': 0.21115067056784395, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.552707016459578}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:17,630] Trial 125 finished with value: 0.8853569770206734 and parameters: {'n_estimators': 288, 'learning_rate': 0.2994230095220126, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.5219698007306968}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:17,858] Trial 126 finished with value: 0.9461482472660036 and parameters: {'n_estimators': 187, 'learning_rate': 0.7884721750296556, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.170239804867078}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:18,074] Trial 127 finished with value: 0.8714309902246997 and parameters: {'n_estimators': 126, 'learning_rate': 0.24054334690540302, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:18,548] Trial 128 finished with value: 0.9012734581578833 and parameters: {'n_estimators': 256, 'learning_rate': 0.38409733682042313, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.4191660723818265}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:18,872] Trial 129 finished with value: 0.9349763660408265 and parameters: {'n_estimators': 193, 'learning_rate': 0.47044486253274354, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0705422821711204}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:19,413] Trial 130 finished with value: 0.9434181820431042 and parameters: {'n_estimators': 176, 'learning_rate': 0.21850684780654933, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.5125467723090513}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:20,153] Trial 131 finished with value: 0.9460737251637724 and parameters: {'n_estimators': 206, 'learning_rate': 0.2531366441565206, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7267950905931142}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:20,897] Trial 132 finished with value: 0.9490707723468574 and parameters: {'n_estimators': 165, 'learning_rate': 0.18760740530924705, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.265656983620488}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:21,743] Trial 133 finished with value: 0.943311571394499 and parameters: {'n_estimators': 164, 'learning_rate': 0.19086079419695584, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.2097265572609297}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:22,476] Trial 134 finished with value: 0.9516409872982872 and parameters: {'n_estimators': 217, 'learning_rate': 0.29735193665249443, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.770599254653628}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:23,321] Trial 135 finished with value: 0.9517444082110016 and parameters: {'n_estimators': 218, 'learning_rate': 0.1632302131953216, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.040113453036413}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:24,014] Trial 136 finished with value: 0.9516815633204476 and parameters: {'n_estimators': 218, 'learning_rate': 0.16882720694545292, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.942970319501494}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:25,170] Trial 137 finished with value: -inf and parameters: {'n_estimators': 247, 'learning_rate': 0.1278287180708752, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 4.846425871954481, 'coef0': 0.25306830107690254}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:25,930] Trial 138 finished with value: 0.946129038490311 and parameters: {'n_estimators': 237, 'learning_rate': 0.10010032101446002, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.968090929872483}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:26,354] Trial 139 finished with value: 0.9463381854964412 and parameters: {'n_estimators': 231, 'learning_rate': 0.15840971565975542, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7352933426106074}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:27,210] Trial 140 finished with value: 0.9460938056940037 and parameters: {'n_estimators': 211, 'learning_rate': 0.17239197988266658, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3235504334453292}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:27,967] Trial 141 finished with value: 0.9487049848424336 and parameters: {'n_estimators': 219, 'learning_rate': 0.21300438495163315, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.790899376657866}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:28,731] Trial 142 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 219, 'learning_rate': 0.23442872811180468, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.6011804785275734}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:29,792] Trial 143 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 264, 'learning_rate': 0.20570915176817917, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8695111203697865}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:30,746] Trial 144 finished with value: 0.9374704190223566 and parameters: {'n_estimators': 195, 'learning_rate': 0.22711948376345956, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.417921813995831}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:31,517] Trial 145 finished with value: 0.9490205693199103 and parameters: {'n_estimators': 220, 'learning_rate': 0.1523444667474847, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.36120407727575}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:32,074] Trial 146 finished with value: 0.946030122496716 and parameters: {'n_estimators': 307, 'learning_rate': 0.24890881861731973, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.228147164535369}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:33,353] Trial 147 finished with value: 0.7023921951486901 and parameters: {'n_estimators': 251, 'learning_rate': 0.18049116357783734, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 2.1660641663421627, 'degree': 2, 'coef0': 0.5060218846433415}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:33,449] Trial 148 finished with value: 0.8791645618408939 and parameters: {'n_estimators': 227, 'learning_rate': 0.13354408856364375, 'algorithm': 'SAMME.R', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 5.979046347062491}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:33,784] Trial 149 finished with value: 0.9054841227029135 and parameters: {'n_estimators': 199, 'learning_rate': 0.16667582378735823, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.4840202886913443}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:34,114] Trial 150 finished with value: 0.9166507172958607 and parameters: {'n_estimators': 186, 'learning_rate': 0.26720591763623947, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.07839370990501919}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:34,758] Trial 151 finished with value: 0.9138729963208455 and parameters: {'n_estimators': 216, 'learning_rate': 0.2302042750507537, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1122679138806006}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:35,507] Trial 152 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 241, 'learning_rate': 0.31520505133488197, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.6944891555683936}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:36,306] Trial 153 finished with value: 0.9461636352536825 and parameters: {'n_estimators': 239, 'learning_rate': 0.3236701702197362, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9127662798338538}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:37,049] Trial 154 finished with value: 0.9462952708457747 and parameters: {'n_estimators': 207, 'learning_rate': 0.3535507455857343, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.58334971605361}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:37,463] Trial 155 finished with value: 0.9461336301867951 and parameters: {'n_estimators': 272, 'learning_rate': 0.5199391044125163, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.676357734051705}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:37,874] Trial 156 finished with value: 0.8602959645297137 and parameters: {'n_estimators': 258, 'learning_rate': 0.27012467250976774, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.0019893842962743474}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:38,092] Trial 157 finished with value: 0.8703560070298408 and parameters: {'n_estimators': 229, 'learning_rate': 0.20094439327024868, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:38,652] Trial 158 finished with value: 0.9435799175554489 and parameters: {'n_estimators': 248, 'learning_rate': 0.24458403490438416, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.4585405054559875}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:39,478] Trial 159 finished with value: 0.9519111763632015 and parameters: {'n_estimators': 206, 'learning_rate': 0.06428014850687971, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.5236712354238175}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:40,291] Trial 160 finished with value: 0.9462496595153113 and parameters: {'n_estimators': 182, 'learning_rate': 0.06148345147359303, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.511917074131766}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:41,296] Trial 161 finished with value: 0.9433997373083892 and parameters: {'n_estimators': 200, 'learning_rate': 0.056282449823456975, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9714411114029415}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:42,007] Trial 162 finished with value: 0.935001884879774 and parameters: {'n_estimators': 210, 'learning_rate': 0.06614387596029363, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7849457122146224}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:42,583] Trial 163 finished with value: 0.9460030266448959 and parameters: {'n_estimators': 223, 'learning_rate': 0.22164397237087538, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.232096588027822}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:43,298] Trial 164 finished with value: 0.9518914317907727 and parameters: {'n_estimators': 242, 'learning_rate': 0.08837430701870018, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.371958876189318}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:44,152] Trial 165 finished with value: 0.9461927188922579 and parameters: {'n_estimators': 238, 'learning_rate': 0.07360033276030915, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.639784254485829}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:45,001] Trial 166 finished with value: 0.9489818082176974 and parameters: {'n_estimators': 254, 'learning_rate': 0.07908133007358858, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.219443385176234}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:45,325] Trial 167 finished with value: 0.9211705188978586 and parameters: {'n_estimators': 189, 'learning_rate': 0.6303367464202104, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.3593735751901277}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:46,049] Trial 168 finished with value: 0.5371120525831441 and parameters: {'n_estimators': 242, 'learning_rate': 0.3106508834294839, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 1.809149011162188, 'coef0': 0.9029906019159136}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:46,522] Trial 169 finished with value: 0.9351877596174386 and parameters: {'n_estimators': 231, 'learning_rate': 0.10364929586198274, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.572489372413239}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:47,500] Trial 170 finished with value: 0.9432840356506091 and parameters: {'n_estimators': 205, 'learning_rate': 0.08771082293345642, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.4686214773634303}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:48,332] Trial 171 finished with value: 0.9462224888474111 and parameters: {'n_estimators': 218, 'learning_rate': 0.23476923003084876, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.830028745713152}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:49,452] Trial 172 finished with value: 0.8773099501946401 and parameters: {'n_estimators': 225, 'learning_rate': 0.06587675146124812, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.016926388284853246}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:49,750] Trial 173 finished with value: 0.9265768775169478 and parameters: {'n_estimators': 197, 'learning_rate': 0.2652275469166709, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8718946130665782}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:50,409] Trial 174 finished with value: 0.9544099308018232 and parameters: {'n_estimators': 280, 'learning_rate': 0.19683229184220954, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2028559208805314}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:51,383] Trial 175 finished with value: 0.9490737209676066 and parameters: {'n_estimators': 281, 'learning_rate': 0.09276801286379756, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.0247920489149362}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:51,733] Trial 176 finished with value: 0.9297117181894698 and parameters: {'n_estimators': 263, 'learning_rate': 0.19306420905714758, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.146986179162074}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:52,924] Trial 177 finished with value: 0.9488718056362714 and parameters: {'n_estimators': 272, 'learning_rate': 0.21075557604381384, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4622172042445536}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:53,812] Trial 178 finished with value: 0.6905746692841864 and parameters: {'n_estimators': 242, 'learning_rate': 0.2472431025104272, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 3.4858813896883194, 'degree': 4, 'coef0': 0.09340899873225705}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:54,022] Trial 179 finished with value: 0.9347568931622089 and parameters: {'n_estimators': 254, 'learning_rate': 0.21538600767079638, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 1.7390434014906178}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:55,197] Trial 180 finished with value: 0.9405344311859402 and parameters: {'n_estimators': 294, 'learning_rate': 0.0476544362356825, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.2260991184797905}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:55,869] Trial 181 finished with value: 0.9490340875605312 and parameters: {'n_estimators': 231, 'learning_rate': 0.181870970871893, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.992069313948637}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:56,653] Trial 182 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 213, 'learning_rate': 0.27280377214301693, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.387474281739788}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:57,258] Trial 183 finished with value: 0.943466304385906 and parameters: {'n_estimators': 205, 'learning_rate': 0.2020747222080973, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.149925894026264}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:57,925] Trial 184 finished with value: 0.9461317097983033 and parameters: {'n_estimators': 191, 'learning_rate': 0.1618939225574238, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.8537724728291467}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:03:58,667] Trial 185 finished with value: 0.9546584631849069 and parameters: {'n_estimators': 388, 'learning_rate': 0.23172077548387995, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.305222179127677}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:00,019] Trial 186 finished with value: 0.9236047324399677 and parameters: {'n_estimators': 246, 'learning_rate': 0.015120439714314308, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 2.1574976046467467}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:00,646] Trial 187 finished with value: 0.943202024996045 and parameters: {'n_estimators': 395, 'learning_rate': 0.2901873392685005, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.6327993424719893}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:02,156] Trial 188 finished with value: 0.9488691343282791 and parameters: {'n_estimators': 413, 'learning_rate': 0.23690288538405274, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9085381101542886}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:02,341] Trial 189 finished with value: 0.8768186259315769 and parameters: {'n_estimators': 347, 'learning_rate': 0.2249297866113301, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:03,570] Trial 190 finished with value: 0.9463066895734725 and parameters: {'n_estimators': 363, 'learning_rate': 0.24692399743713445, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 4.70397135863975}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:04,467] Trial 191 finished with value: 0.9517125575717025 and parameters: {'n_estimators': 405, 'learning_rate': 0.18927762197960674, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.0371730069380747}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:05,529] Trial 192 finished with value: 0.957290655564415 and parameters: {'n_estimators': 391, 'learning_rate': 0.186134731096261, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1592388038658434}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:05,912] Trial 193 finished with value: 0.9195083329662423 and parameters: {'n_estimators': 377, 'learning_rate': 0.26404661468696655, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.14635960598805775}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:06,997] Trial 194 finished with value: 0.951698100788148 and parameters: {'n_estimators': 389, 'learning_rate': 0.21110976555505545, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4076903818873254}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:07,849] Trial 195 finished with value: 0.9462224888474111 and parameters: {'n_estimators': 383, 'learning_rate': 0.29013599820311725, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7990081861455174}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:08,719] Trial 196 finished with value: 0.951896719579647 and parameters: {'n_estimators': 397, 'learning_rate': 0.07357902059935685, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.5500892801338229}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:09,593] Trial 197 finished with value: 0.954692128744154 and parameters: {'n_estimators': 397, 'learning_rate': 0.0743400250121961, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.439866900092313}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:10,153] Trial 198 finished with value: 0.9407596316566416 and parameters: {'n_estimators': 418, 'learning_rate': 0.07062926587315435, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.3067035030172236}. Best is trial 86 with value: 0.9573878203541313.\n", - "[I 2025-08-19 22:04:10,880] Trial 199 finished with value: 0.9519222629510324 and parameters: {'n_estimators': 405, 'learning_rate': 0.07803729201336104, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.4508904105515619}. Best is trial 86 with value: 0.9573878203541313.\n" - ] + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\", message=\".*ignore_implicit_zeros.*\")\n", + "warnings.filterwarnings(\"ignore\", message=\".*n_quantiles.*\")\n", + "warnings.filterwarnings(\"ignore\", category=RuntimeWarning)\n", + "warnings.filterwarnings(\"ignore\", category=FutureWarning)" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Best trial:\n", - " Value (F1 Score): 0.9574\n", - " Parameters: \n", - " n_estimators: 193\n", - " learning_rate: 0.26419239924556914\n", - " algorithm: SAMME\n", - " scaler: minmax\n", - " kernel: rbf\n", - " gamma: 2.768323929854739\n" - ] - } - ], - "source": [ - "import optuna\n", - "import numpy as np\n", - "\n", - "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", - "from sklearn.preprocessing import OneHotEncoder\n", - "from sklearn.compose import ColumnTransformer, make_column_selector\n", - "from sklearn.pipeline import Pipeline\n", - "\n", - "# X, y assumed pre-defined (raw, with object/category cols intact)\n", - "\n", - "\n", - "def custom_loss(y_true, y_pred, weights):\n", - " return np.mean(weights * (y_true - y_pred) ** 2)\n", - "\n", - "\n", - "def _make_preprocessor() -> ColumnTransformer:\n", - " \"\"\"\n", - " Creates a preprocessor that only one-hot encodes categorical features\n", - " and passes numerical features through without scaling.\n", - " \"\"\"\n", - " return ColumnTransformer(\n", - " transformers=[\n", - " # The \"cat\" transformer applies OneHotEncoder to columns of type object or category.\n", - " (\n", - " \"cat\",\n", - " OneHotEncoder(handle_unknown=\"ignore\"),\n", - " make_column_selector(dtype_include=[\"object\", \"category\"]),\n", - " ),\n", - " ],\n", - " # 'remainder=\"passthrough\"' ensures that all other columns (i.e., numerical ones) are kept.\n", - " remainder=\"passthrough\",\n", - " n_jobs=None,\n", - " )\n", - "\n", - "\n", - "def objective(trial):\n", - " \"\"\"\n", - " Optuna objective function for hyperparameter tuning.\n", - " \"\"\"\n", - " # Define the search space for the classifier's parameters.\n", - " # The \"scaler\" parameter has been removed.\n", - " params = {\n", - " \"n_estimators\": trial.suggest_int(\"n_estimators\", 10, 500),\n", - " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 1.0, log=True),\n", - " \"algorithm\": trial.suggest_categorical(\"algorithm\", [\"SAMME\", \"SAMME.R\"]),\n", - " \"scaler\": trial.suggest_categorical(\n", - " \"scaler\", [\"minmax\", \"robust\", \"quantile-uniform\", \"quantile-normal\"]\n", - " ),\n", - " \"kernel\": trial.suggest_categorical(\n", - " \"kernel\", [\"linear\", \"rbf\", \"poly\", \"sigmoid\"]\n", - " ),\n", - " }\n", - " # Conditionally add parameters based on the chosen kernel.\n", - " if params[\"kernel\"] != \"linear\":\n", - " params[\"gamma\"] = trial.suggest_float(\"gamma\", 1e-3, 10.0, log=True)\n", - " if params[\"kernel\"] == \"poly\":\n", - " params[\"degree\"] = trial.suggest_int(\"degree\", 2, 5)\n", - " if params[\"kernel\"] in [\"poly\", \"sigmoid\"]:\n", - " params[\"coef0\"] = trial.suggest_float(\"coef0\", 0.0, 1.0)\n", - "\n", - " # Build a leakage-free pipeline for the trial.\n", - " # The preprocessor no longer requires a scaler argument.\n", - " pre = _make_preprocessor()\n", - "\n", - " # All items in `params` are now intended for the classifier.\n", - " clf = LinearBoostClassifier(**params)\n", - "\n", - " pipe = Pipeline(steps=[(\"preprocess\", pre), (\"model\", clf)])\n", - "\n", - " try:\n", - " # Perform stratified 10-fold cross-validation.\n", - " cv = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n", - " scores = cross_val_score(pipe, X, y, scoring=\"f1_weighted\", cv=cv)\n", - " # Return the mean F1 score, or negative infinity if scores contain NaN.\n", - " return -np.inf if np.isnan(scores).any() else scores.mean()\n", - " except Exception as e:\n", - " # Prune trial if an exception occurs (e.g., invalid parameter combination).\n", - " print(f\"Trial failed with exception: {e}\")\n", - " return -np.inf\n", - "\n", - "\n", - "# --- Optuna Study Execution ---\n", - "# Create a study object and specify the direction as \"maximize\" for F1 score.\n", - "study = optuna.create_study(direction=\"maximize\")\n", - "study.optimize(objective, n_trials=200)\n", - "\n", - "# --- Print Best Results ---\n", - "print(\"\\nBest trial:\")\n", - "best_trial = study.best_trial\n", - "print(f\" Value (F1 Score): {best_trial.value:.4f}\")\n", - "print(\" Parameters: \")\n", - "for key, value in best_trial.params.items():\n", - " print(f\" {key}: {value}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**XGBoost results:**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-18 23:04:37,538] A new study created in memory with name: no-name-a6ac08d4-0166-4e55-82db-e34c20f65e38\n", - "[I 2025-08-18 23:04:38,723] Trial 0 finished with value: 0.9636743691091517 and parameters: {'n_estimators': 793, 'max_depth': 16, 'learning_rate': 0.08966826500844771, 'gamma': 1.5332174950801975e-05, 'min_child_weight': 7, 'subsample': 0.8206767596857434, 'colsample_bytree': 0.5726809729609164, 'reg_alpha': 0.3000662922036043, 'reg_lambda': 6.694076855447791e-06}. Best is trial 0 with value: 0.9636743691091517.\n", - "[I 2025-08-18 23:04:39,297] Trial 1 finished with value: 0.92515962298571 and parameters: {'n_estimators': 363, 'max_depth': 1, 'learning_rate': 0.6923884519284504, 'gamma': 2.3719556857557514e-07, 'min_child_weight': 9, 'subsample': 0.5195696271131344, 'colsample_bytree': 0.9721890311504119, 'reg_alpha': 0.0004982860931446735, 'reg_lambda': 4.9598622967800296e-08}. Best is trial 0 with value: 0.9636743691091517.\n", - "[I 2025-08-18 23:04:39,907] Trial 2 finished with value: 0.9660813823857302 and parameters: {'n_estimators': 765, 'max_depth': 19, 'learning_rate': 0.03328962689146766, 'gamma': 0.005416426649707568, 'min_child_weight': 5, 'subsample': 0.8716669106394426, 'colsample_bytree': 0.619605690338052, 'reg_alpha': 0.1588033011486252, 'reg_lambda': 0.10090421373216449}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:39,956] Trial 3 finished with value: 0.9646701124961995 and parameters: {'n_estimators': 162, 'max_depth': 14, 'learning_rate': 0.22096268147375914, 'gamma': 0.20303915469434114, 'min_child_weight': 3, 'subsample': 0.7816550027087239, 'colsample_bytree': 0.9440324292952285, 'reg_alpha': 0.00019615793084263862, 'reg_lambda': 0.00012620616546111783}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,531] Trial 4 finished with value: 0.9618906455862977 and parameters: {'n_estimators': 746, 'max_depth': 5, 'learning_rate': 0.27373124279594174, 'gamma': 5.113866726169806e-07, 'min_child_weight': 8, 'subsample': 0.9786346051499656, 'colsample_bytree': 0.817382203507034, 'reg_alpha': 0.00010865601540579662, 'reg_lambda': 0.7028348077651659}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,571] Trial 5 finished with value: 0.9375772777946689 and parameters: {'n_estimators': 131, 'max_depth': 9, 'learning_rate': 0.6666830358877334, 'gamma': 2.3337802367945706e-06, 'min_child_weight': 10, 'subsample': 0.5767815340215819, 'colsample_bytree': 0.8847564080638974, 'reg_alpha': 1.1720116806607218e-05, 'reg_lambda': 0.00014985518222546636}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,647] Trial 6 finished with value: 0.9322793148880105 and parameters: {'n_estimators': 811, 'max_depth': 19, 'learning_rate': 0.6284423078537571, 'gamma': 2.5468120149201276e-08, 'min_child_weight': 8, 'subsample': 0.5241240142259422, 'colsample_bytree': 0.7077124133325703, 'reg_alpha': 0.00122899449385656, 'reg_lambda': 4.150700737033019e-05}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,675] Trial 7 finished with value: 0.9404048849701023 and parameters: {'n_estimators': 55, 'max_depth': 8, 'learning_rate': 0.6143004867698488, 'gamma': 0.0013027026334781191, 'min_child_weight': 7, 'subsample': 0.6231620588280503, 'colsample_bytree': 0.8828670937564691, 'reg_alpha': 2.9404686235297146e-07, 'reg_lambda': 3.754444639692557e-06}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,740] Trial 8 finished with value: 0.9578595317725753 and parameters: {'n_estimators': 499, 'max_depth': 18, 'learning_rate': 0.5646291569978734, 'gamma': 1.7349709546981462e-05, 'min_child_weight': 2, 'subsample': 0.8928178421726397, 'colsample_bytree': 0.6848598778618181, 'reg_alpha': 0.5610745294606653, 'reg_lambda': 0.5364150960157834}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,805] Trial 9 finished with value: 0.9590174318435187 and parameters: {'n_estimators': 699, 'max_depth': 4, 'learning_rate': 0.31764392327897784, 'gamma': 0.11453542510872944, 'min_child_weight': 10, 'subsample': 0.7055074511257982, 'colsample_bytree': 0.796546556661627, 'reg_alpha': 2.907763331398582e-05, 'reg_lambda': 2.2504856133119337e-05}. Best is trial 2 with value: 0.9660813823857302.\n", - "[I 2025-08-18 23:04:40,963] Trial 10 finished with value: 0.9670897942637072 and parameters: {'n_estimators': 972, 'max_depth': 13, 'learning_rate': 0.02160073099534278, 'gamma': 0.0012263645582748532, 'min_child_weight': 4, 'subsample': 0.9792412216883989, 'colsample_bytree': 0.520612587086734, 'reg_alpha': 0.013660705792304169, 'reg_lambda': 0.011791232435673288}. Best is trial 10 with value: 0.9670897942637072.\n", - "[I 2025-08-18 23:04:41,107] Trial 11 finished with value: 0.9643077936556198 and parameters: {'n_estimators': 950, 'max_depth': 12, 'learning_rate': 0.02786001957318099, 'gamma': 0.0017314307200539348, 'min_child_weight': 4, 'subsample': 0.9907050379036834, 'colsample_bytree': 0.5125919786788546, 'reg_alpha': 0.01547481122556199, 'reg_lambda': 0.021894838205846742}. Best is trial 10 with value: 0.9670897942637072.\n", - "[I 2025-08-18 23:04:41,213] Trial 12 finished with value: 0.9663930272625926 and parameters: {'n_estimators': 993, 'max_depth': 20, 'learning_rate': 0.14543560489328874, 'gamma': 0.0033996503304433074, 'min_child_weight': 5, 'subsample': 0.8889007946941537, 'colsample_bytree': 0.6084715786342512, 'reg_alpha': 0.022413404033686066, 'reg_lambda': 0.011064527798418372}. Best is trial 10 with value: 0.9670897942637072.\n", - "[I 2025-08-18 23:04:41,322] Trial 13 finished with value: 0.968164082294517 and parameters: {'n_estimators': 955, 'max_depth': 14, 'learning_rate': 0.1639284511998979, 'gamma': 0.0002751891194586191, 'min_child_weight': 1, 'subsample': 0.9147497384875082, 'colsample_bytree': 0.5126649768955113, 'reg_alpha': 0.016597036392593374, 'reg_lambda': 0.004707104171200651}. Best is trial 13 with value: 0.968164082294517.\n", - "[I 2025-08-18 23:04:41,408] Trial 14 finished with value: 0.9720735785953177 and parameters: {'n_estimators': 635, 'max_depth': 12, 'learning_rate': 0.44435309051067096, 'gamma': 0.0006644642045654169, 'min_child_weight': 1, 'subsample': 0.9432618865143836, 'colsample_bytree': 0.5039154540738406, 'reg_alpha': 0.004876635115949546, 'reg_lambda': 0.0064355512337324105}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,484] Trial 15 finished with value: 0.9674521131042871 and parameters: {'n_estimators': 569, 'max_depth': 10, 'learning_rate': 0.43787269752034375, 'gamma': 0.00011195314945572638, 'min_child_weight': 1, 'subsample': 0.7069629644516782, 'colsample_bytree': 0.5634075101229923, 'reg_alpha': 4.464784207396974e-08, 'reg_lambda': 0.003997182136400165}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,558] Trial 16 finished with value: 0.9707433870477349 and parameters: {'n_estimators': 370, 'max_depth': 15, 'learning_rate': 0.4599427117745171, 'gamma': 8.735091706299628e-05, 'min_child_weight': 1, 'subsample': 0.9257669635457493, 'colsample_bytree': 0.6689607583849055, 'reg_alpha': 0.003005669831594476, 'reg_lambda': 0.0009691828324956179}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,631] Trial 17 finished with value: 0.9679563190432756 and parameters: {'n_estimators': 336, 'max_depth': 16, 'learning_rate': 0.4272808911789559, 'gamma': 1.1267461214053029e-05, 'min_child_weight': 2, 'subsample': 0.8380523208836226, 'colsample_bytree': 0.672358753892155, 'reg_alpha': 3.5941246015085105e-06, 'reg_lambda': 0.0012762246601831144}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,703] Trial 18 finished with value: 0.962460727678119 and parameters: {'n_estimators': 412, 'max_depth': 7, 'learning_rate': 0.4945841962092967, 'gamma': 0.7046722512199631, 'min_child_weight': 2, 'subsample': 0.9443084841264685, 'colsample_bytree': 0.752150502842086, 'reg_alpha': 0.0022930157034841687, 'reg_lambda': 0.0005914759736460705}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,781] Trial 19 finished with value: 0.9693523867436911 and parameters: {'n_estimators': 603, 'max_depth': 11, 'learning_rate': 0.4182386109054242, 'gamma': 0.02844656967423761, 'min_child_weight': 3, 'subsample': 0.7636043135868457, 'colsample_bytree': 0.6293491016063527, 'reg_alpha': 0.002891811181173915, 'reg_lambda': 6.079751271976952e-07}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,844] Trial 20 finished with value: 0.9646321070234114 and parameters: {'n_estimators': 263, 'max_depth': 16, 'learning_rate': 0.5343710663782837, 'gamma': 0.00020994204354847013, 'min_child_weight': 1, 'subsample': 0.933551117358393, 'colsample_bytree': 0.7553892763360576, 'reg_alpha': 1.4227453672543946e-06, 'reg_lambda': 0.07295757354368651}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:41,929] Trial 21 finished with value: 0.9683287726765988 and parameters: {'n_estimators': 618, 'max_depth': 11, 'learning_rate': 0.39203875257523096, 'gamma': 0.020660444962692592, 'min_child_weight': 3, 'subsample': 0.7522258388072962, 'colsample_bytree': 0.6287497031716449, 'reg_alpha': 0.0027780793331277473, 'reg_lambda': 4.744211463091777e-07}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,003] Trial 22 finished with value: 0.9650729705077531 and parameters: {'n_estimators': 479, 'max_depth': 11, 'learning_rate': 0.4816697063234048, 'gamma': 0.02294520899250463, 'min_child_weight': 3, 'subsample': 0.8261862173185567, 'colsample_bytree': 0.6535905438209455, 'reg_alpha': 0.05648104038500446, 'reg_lambda': 7.945709365351044e-08}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,087] Trial 23 finished with value: 0.9649690888821322 and parameters: {'n_estimators': 617, 'max_depth': 14, 'learning_rate': 0.35399121863614574, 'gamma': 0.023886459668739847, 'min_child_weight': 1, 'subsample': 0.6707746880436944, 'colsample_bytree': 0.5755080172718738, 'reg_alpha': 0.004076372892245553, 'reg_lambda': 9.163582970819522e-07}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,163] Trial 24 finished with value: 0.9611761426978817 and parameters: {'n_estimators': 443, 'max_depth': 12, 'learning_rate': 0.3139681715812469, 'gamma': 0.0003768107966552948, 'min_child_weight': 2, 'subsample': 0.785577063811775, 'colsample_bytree': 0.7035064694391241, 'reg_alpha': 0.0002961952288355031, 'reg_lambda': 0.0007189349722448769}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,226] Trial 25 finished with value: 0.9621769534813012 and parameters: {'n_estimators': 270, 'max_depth': 17, 'learning_rate': 0.46661524082093503, 'gamma': 3.724723823557411e-05, 'min_child_weight': 4, 'subsample': 0.8543235968447394, 'colsample_bytree': 0.5745613732539564, 'reg_alpha': 5.043186797452251e-05, 'reg_lambda': 1.0823805710576936e-08}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,310] Trial 26 finished with value: 0.967454646802473 and parameters: {'n_estimators': 571, 'max_depth': 7, 'learning_rate': 0.39555431045443845, 'gamma': 0.010531397617842813, 'min_child_weight': 3, 'subsample': 0.9520895450331223, 'colsample_bytree': 0.6505146452181498, 'reg_alpha': 0.07277660854823283, 'reg_lambda': 0.00017848811714192225}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,407] Trial 27 finished with value: 0.971115840681058 and parameters: {'n_estimators': 886, 'max_depth': 15, 'learning_rate': 0.5596905359749961, 'gamma': 0.109957517842398, 'min_child_weight': 1, 'subsample': 0.911463740843732, 'colsample_bytree': 0.7242482520459889, 'reg_alpha': 0.004304571005570774, 'reg_lambda': 0.0019289290476947067}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,567] Trial 28 finished with value: 0.9622124252559034 and parameters: {'n_estimators': 856, 'max_depth': 15, 'learning_rate': 0.5491779113793174, 'gamma': 0.9394863827667955, 'min_child_weight': 1, 'subsample': 0.9085194590375377, 'colsample_bytree': 0.8008991430166865, 'reg_alpha': 0.0007901559140269053, 'reg_lambda': 0.0017254433653291876}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,670] Trial 29 finished with value: 0.9647359886490323 and parameters: {'n_estimators': 862, 'max_depth': 17, 'learning_rate': 0.5820996718221064, 'gamma': 5.022199051728779e-06, 'min_child_weight': 6, 'subsample': 0.8071126403433657, 'colsample_bytree': 0.8688765430232145, 'reg_alpha': 0.6743398600163427, 'reg_lambda': 0.07862706605671561}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,758] Trial 30 finished with value: 0.9642292490118578 and parameters: {'n_estimators': 709, 'max_depth': 13, 'learning_rate': 0.5155202664068682, 'gamma': 5.8451733953677565e-05, 'min_child_weight': 2, 'subsample': 0.9509763250842893, 'colsample_bytree': 0.7129940865613236, 'reg_alpha': 0.008859259561073272, 'reg_lambda': 3.4509898100450316e-05}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,845] Trial 31 finished with value: 0.9657722712070538 and parameters: {'n_estimators': 668, 'max_depth': 10, 'learning_rate': 0.4395334552771406, 'gamma': 0.12712718293414763, 'min_child_weight': 1, 'subsample': 0.9988158980266512, 'colsample_bytree': 0.5936405830531623, 'reg_alpha': 0.004952419311036929, 'reg_lambda': 6.401818643223202e-06}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,919] Trial 32 finished with value: 0.961406709232796 and parameters: {'n_estimators': 566, 'max_depth': 15, 'learning_rate': 0.3597185445003348, 'gamma': 0.052315813645452125, 'min_child_weight': 2, 'subsample': 0.861533388856762, 'colsample_bytree': 0.5482756215722395, 'reg_alpha': 0.0008797977184427369, 'reg_lambda': 0.000414443174592793}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:42,983] Trial 33 finished with value: 0.9657722712070539 and parameters: {'n_estimators': 356, 'max_depth': 12, 'learning_rate': 0.5063187891048766, 'gamma': 0.0006293033474033146, 'min_child_weight': 3, 'subsample': 0.9245516224148534, 'colsample_bytree': 0.7700173552170951, 'reg_alpha': 0.1375518302261409, 'reg_lambda': 0.0033261674432578194}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:43,056] Trial 34 finished with value: 0.9628433161041858 and parameters: {'n_estimators': 281, 'max_depth': 15, 'learning_rate': 0.39986529526862014, 'gamma': 0.33270406488078025, 'min_child_weight': 1, 'subsample': 0.8777255486034471, 'colsample_bytree': 0.6377133084935319, 'reg_alpha': 0.00040666270333044826, 'reg_lambda': 0.01722992299278233}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:43,143] Trial 35 finished with value: 0.9677789601702645 and parameters: {'n_estimators': 809, 'max_depth': 13, 'learning_rate': 0.5932469392267316, 'gamma': 0.006088499877130821, 'min_child_weight': 2, 'subsample': 0.7328484494819534, 'colsample_bytree': 0.7319378460341505, 'reg_alpha': 0.05604671729670822, 'reg_lambda': 0.00026653903767523407}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:43,242] Trial 36 finished with value: 0.9578975372453634 and parameters: {'n_estimators': 894, 'max_depth': 17, 'learning_rate': 0.6747312199854105, 'gamma': 1.4778405111109977e-06, 'min_child_weight': 4, 'subsample': 0.8061783788836056, 'colsample_bytree': 0.6785763400584698, 'reg_alpha': 0.00011687995768555662, 'reg_lambda': 0.23451609747860863}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:43,305] Trial 37 finished with value: 0.9607327455153543 and parameters: {'n_estimators': 416, 'max_depth': 1, 'learning_rate': 0.4620319359751538, 'gamma': 0.060081915589133755, 'min_child_weight': 3, 'subsample': 0.9671673389437769, 'colsample_bytree': 0.5439077141472997, 'reg_alpha': 0.0016050980147079938, 'reg_lambda': 0.03470161515812803}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:43,391] Trial 38 finished with value: 0.9623315090706395 and parameters: {'n_estimators': 741, 'max_depth': 9, 'learning_rate': 0.26537466239492763, 'gamma': 3.8588922199082426e-08, 'min_child_weight': 6, 'subsample': 0.6229188943554498, 'colsample_bytree': 0.8482038406619968, 'reg_alpha': 0.005961031499798193, 'reg_lambda': 9.178673123098809e-05}. Best is trial 14 with value: 0.9720735785953177.\n", - "[I 2025-08-18 23:04:43,453] Trial 39 finished with value: 0.9733835005574136 and parameters: {'n_estimators': 174, 'max_depth': 9, 'learning_rate': 0.3415861867273047, 'gamma': 0.00320158129516171, 'min_child_weight': 1, 'subsample': 0.7657875222614208, 'colsample_bytree': 0.6055391800615106, 'reg_alpha': 0.1961144247885326, 'reg_lambda': 1.3349872128243998e-05}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,528] Trial 40 finished with value: 0.968103273538056 and parameters: {'n_estimators': 194, 'max_depth': 5, 'learning_rate': 0.2308941510629727, 'gamma': 0.002267995615949968, 'min_child_weight': 1, 'subsample': 0.907878075061457, 'colsample_bytree': 0.9968707460456452, 'reg_alpha': 0.18618906668818894, 'reg_lambda': 1.9657102325946478e-05}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,569] Trial 41 finished with value: 0.9706876456876458 and parameters: {'n_estimators': 26, 'max_depth': 9, 'learning_rate': 0.3394366537016498, 'gamma': 0.0075177253863414695, 'min_child_weight': 2, 'subsample': 0.7720455412614378, 'colsample_bytree': 0.607113034664798, 'reg_alpha': 0.02755418326100873, 'reg_lambda': 1.6417879593738852e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,622] Trial 42 finished with value: 0.9656278504104592 and parameters: {'n_estimators': 28, 'max_depth': 8, 'learning_rate': 0.3375467490973728, 'gamma': 0.008183578589292693, 'min_child_weight': 2, 'subsample': 0.7841595414778176, 'colsample_bytree': 0.6001413581900443, 'reg_alpha': 0.039635394071934116, 'reg_lambda': 1.820175490207568e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,686] Trial 43 finished with value: 0.9674166413296849 and parameters: {'n_estimators': 92, 'max_depth': 9, 'learning_rate': 0.2951892312329311, 'gamma': 0.0011926871557951385, 'min_child_weight': 1, 'subsample': 0.7243233789331518, 'colsample_bytree': 0.6690830197165509, 'reg_alpha': 0.2981096546445941, 'reg_lambda': 1.4732474336111884e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,737] Trial 44 finished with value: 0.9664665045099827 and parameters: {'n_estimators': 176, 'max_depth': 3, 'learning_rate': 0.3778692466816108, 'gamma': 0.0006795734196391805, 'min_child_weight': 2, 'subsample': 0.846170946192214, 'colsample_bytree': 0.5421093232735782, 'reg_alpha': 0.1171370589737971, 'reg_lambda': 9.218742520129267e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,790] Trial 45 finished with value: 0.9642292490118578 and parameters: {'n_estimators': 112, 'max_depth': 6, 'learning_rate': 0.26260487033994784, 'gamma': 0.00011851832743201036, 'min_child_weight': 1, 'subsample': 0.670336459772904, 'colsample_bytree': 0.7208950473295055, 'reg_alpha': 0.02908781781480345, 'reg_lambda': 6.543787850283628e-05}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,852] Trial 46 finished with value: 0.96029948312557 and parameters: {'n_estimators': 220, 'max_depth': 9, 'learning_rate': 0.6312256464453558, 'gamma': 0.0036712637572776517, 'min_child_weight': 1, 'subsample': 0.8759520439984964, 'colsample_bytree': 0.6914986554072519, 'reg_alpha': 0.3474285764344179, 'reg_lambda': 0.006752518206121544}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,904] Trial 47 finished with value: 0.9499163879598662 and parameters: {'n_estimators': 146, 'max_depth': 19, 'learning_rate': 0.20922691721035272, 'gamma': 3.8419590657259207e-05, 'min_child_weight': 8, 'subsample': 0.5049535044393377, 'colsample_bytree': 0.9226368889131558, 'reg_alpha': 0.010213751761400837, 'reg_lambda': 0.0014363034008709101}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:43,969] Trial 48 finished with value: 0.9649412182020877 and parameters: {'n_estimators': 64, 'max_depth': 8, 'learning_rate': 0.07577872858481222, 'gamma': 0.2638175764876564, 'min_child_weight': 2, 'subsample': 0.963968884483731, 'colsample_bytree': 0.5924098530493901, 'reg_alpha': 0.999637524746841, 'reg_lambda': 2.0261391177441924e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,033] Trial 49 finished with value: 0.9655645079558124 and parameters: {'n_estimators': 318, 'max_depth': 14, 'learning_rate': 0.33052174325673006, 'gamma': 0.011942467037248633, 'min_child_weight': 1, 'subsample': 0.6627788600351412, 'colsample_bytree': 0.6141066675957493, 'reg_alpha': 0.021696432447302145, 'reg_lambda': 1.0007983816416382e-05}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,088] Trial 50 finished with value: 0.9663803587716633 and parameters: {'n_estimators': 236, 'max_depth': 10, 'learning_rate': 0.45078154977126994, 'gamma': 1.5117023515346045e-05, 'min_child_weight': 2, 'subsample': 0.5688408997309418, 'colsample_bytree': 0.5299284944128524, 'reg_alpha': 1.8494068989589203e-08, 'reg_lambda': 0.0022820773871882346}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,161] Trial 51 finished with value: 0.9703557312252965 and parameters: {'n_estimators': 512, 'max_depth': 11, 'learning_rate': 0.5295370440664156, 'gamma': 0.06319050293389655, 'min_child_weight': 3, 'subsample': 0.7545681529668761, 'colsample_bytree': 0.6317023972454394, 'reg_alpha': 0.0015414355079223494, 'reg_lambda': 4.324091704580854e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,237] Trial 52 finished with value: 0.9709663524880916 and parameters: {'n_estimators': 514, 'max_depth': 12, 'learning_rate': 0.5300714512293007, 'gamma': 0.06686213254636227, 'min_child_weight': 2, 'subsample': 0.7598964166427791, 'colsample_bytree': 0.6527821461167355, 'reg_alpha': 0.0007257680068320631, 'reg_lambda': 2.053211374630651e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,301] Trial 53 finished with value: 0.9352690787473396 and parameters: {'n_estimators': 506, 'max_depth': 12, 'learning_rate': 0.571256600848416, 'gamma': 0.004555999545517148, 'min_child_weight': 9, 'subsample': 0.7047240133608822, 'colsample_bytree': 0.5018984188314298, 'reg_alpha': 0.0005907798905113109, 'reg_lambda': 2.4734342938311394e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,375] Trial 54 finished with value: 0.9644775514340731 and parameters: {'n_estimators': 395, 'max_depth': 13, 'learning_rate': 0.6124317734833269, 'gamma': 0.00048108720311051555, 'min_child_weight': 1, 'subsample': 0.7718507840031281, 'colsample_bytree': 0.6489094093412939, 'reg_alpha': 0.00010645026093228777, 'reg_lambda': 3.4160412117423306e-08}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,451] Trial 55 finished with value: 0.9688887199756765 and parameters: {'n_estimators': 463, 'max_depth': 18, 'learning_rate': 0.4202773904272926, 'gamma': 0.12392807749675176, 'min_child_weight': 2, 'subsample': 0.8134953557614573, 'colsample_bytree': 0.5607537502942631, 'reg_alpha': 0.00023820341543495421, 'reg_lambda': 2.1461245433286342e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,541] Trial 56 finished with value: 0.9663702239789196 and parameters: {'n_estimators': 669, 'max_depth': 10, 'learning_rate': 0.48574283632282905, 'gamma': 0.4148692898234699, 'min_child_weight': 1, 'subsample': 0.7307151250713312, 'colsample_bytree': 0.6678470212859086, 'reg_alpha': 0.008252969517073406, 'reg_lambda': 1.1251409603467727e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,616] Trial 57 finished with value: 0.9625139353400222 and parameters: {'n_estimators': 525, 'max_depth': 7, 'learning_rate': 0.5519120903294772, 'gamma': 0.0001874680975299932, 'min_child_weight': 5, 'subsample': 0.8900352044342466, 'colsample_bytree': 0.6932159225648519, 'reg_alpha': 0.002517108855212675, 'reg_lambda': 4.297366901491959e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,682] Trial 58 finished with value: 0.966405695753522 and parameters: {'n_estimators': 306, 'max_depth': 15, 'learning_rate': 0.3674085407668765, 'gamma': 0.0017976084371012489, 'min_child_weight': 2, 'subsample': 0.824737146000951, 'colsample_bytree': 0.7399794252049822, 'reg_alpha': 0.015847378796743628, 'reg_lambda': 0.0005358852795940928}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,783] Trial 59 finished with value: 0.9697856491334752 and parameters: {'n_estimators': 774, 'max_depth': 13, 'learning_rate': 0.6457443852498842, 'gamma': 0.012496329388736885, 'min_child_weight': 1, 'subsample': 0.793838230860561, 'colsample_bytree': 0.5836425111317189, 'reg_alpha': 2.1754437677486564e-05, 'reg_lambda': 0.03337705451236421}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,846] Trial 60 finished with value: 0.963887199756765 and parameters: {'n_estimators': 382, 'max_depth': 12, 'learning_rate': 0.47328611057555103, 'gamma': 0.0424604798937201, 'min_child_weight': 4, 'subsample': 0.934552791164968, 'colsample_bytree': 0.7790054412552747, 'reg_alpha': 0.0011101990270547515, 'reg_lambda': 1.6827865084742688e-05}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,925] Trial 61 finished with value: 0.9660205736292694 and parameters: {'n_estimators': 545, 'max_depth': 11, 'learning_rate': 0.5055055462729076, 'gamma': 0.18056516452373952, 'min_child_weight': 3, 'subsample': 0.7519924075640182, 'colsample_bytree': 0.6178207309513841, 'reg_alpha': 0.0020172691789128233, 'reg_lambda': 3.9215049717299714e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:44,998] Trial 62 finished with value: 0.9557236242018851 and parameters: {'n_estimators': 473, 'max_depth': 11, 'learning_rate': 0.5400019943938102, 'gamma': 0.07754945232934854, 'min_child_weight': 2, 'subsample': 0.691256641899452, 'colsample_bytree': 0.6416326406060736, 'reg_alpha': 0.003532251580912962, 'reg_lambda': 1.0910716788302746e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,075] Trial 63 finished with value: 0.9659648322691801 and parameters: {'n_estimators': 640, 'max_depth': 10, 'learning_rate': 0.5246673195092458, 'gamma': 0.017184255393415157, 'min_child_weight': 1, 'subsample': 0.7639435627387441, 'colsample_bytree': 0.660278919577028, 'reg_alpha': 0.0005455413550718301, 'reg_lambda': 1.917088427074494e-08}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,139] Trial 64 finished with value: 0.964343265430222 and parameters: {'n_estimators': 442, 'max_depth': 14, 'learning_rate': 0.6003911375434905, 'gamma': 0.037188909985777056, 'min_child_weight': 3, 'subsample': 0.8347898516250483, 'colsample_bytree': 0.6269187811627178, 'reg_alpha': 0.0011552312420663807, 'reg_lambda': 2.833228903339653e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,180] Trial 65 finished with value: 0.9688912536738623 and parameters: {'n_estimators': 27, 'max_depth': 16, 'learning_rate': 0.2882497364553881, 'gamma': 0.0009365344901339396, 'min_child_weight': 2, 'subsample': 0.7470376879442628, 'colsample_bytree': 0.7041041755942481, 'reg_alpha': 0.08121948743500555, 'reg_lambda': 5.089309275914002e-08}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,281] Trial 66 finished with value: 0.9698261883044491 and parameters: {'n_estimators': 580, 'max_depth': 9, 'learning_rate': 0.4159616356940845, 'gamma': 0.5831219162124316, 'min_child_weight': 1, 'subsample': 0.982382322395441, 'colsample_bytree': 0.6102710521767731, 'reg_alpha': 0.0059321708676018815, 'reg_lambda': 0.005835785017549864}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,358] Trial 67 finished with value: 0.9618602412080672 and parameters: {'n_estimators': 534, 'max_depth': 8, 'learning_rate': 0.5710556707328297, 'gamma': 0.09669043321056411, 'min_child_weight': 3, 'subsample': 0.9073873458628307, 'colsample_bytree': 0.6799121381784294, 'reg_alpha': 0.0363553592541077, 'reg_lambda': 0.0010027836004984157}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,457] Trial 68 finished with value: 0.967196209587514 and parameters: {'n_estimators': 936, 'max_depth': 12, 'learning_rate': 0.49474283126858015, 'gamma': 0.0038977451885714052, 'min_child_weight': 2, 'subsample': 0.718024396773361, 'colsample_bytree': 0.5552789770779454, 'reg_alpha': 0.00037830643324867133, 'reg_lambda': 1.1088488335267902e-06}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,510] Trial 69 finished with value: 0.955052194182629 and parameters: {'n_estimators': 113, 'max_depth': 14, 'learning_rate': 0.5265511334361885, 'gamma': 0.002516218958369442, 'min_child_weight': 1, 'subsample': 0.7984530114493523, 'colsample_bytree': 0.7246949533111133, 'reg_alpha': 0.009898780192040475, 'reg_lambda': 0.0002248622535206601}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,573] Trial 70 finished with value: 0.9673761021587108 and parameters: {'n_estimators': 361, 'max_depth': 11, 'learning_rate': 0.4500338383720486, 'gamma': 7.97419217113888e-05, 'min_child_weight': 1, 'subsample': 0.7758735699887569, 'colsample_bytree': 0.6353171405510678, 'reg_alpha': 0.003990138744326455, 'reg_lambda': 6.367408215373258e-07}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,661] Trial 71 finished with value: 0.9699883449883451 and parameters: {'n_estimators': 574, 'max_depth': 9, 'learning_rate': 0.39331230829103997, 'gamma': 0.5832162124136367, 'min_child_weight': 1, 'subsample': 0.9892047975972974, 'colsample_bytree': 0.6070149608820187, 'reg_alpha': 0.005905898119536387, 'reg_lambda': 0.006704882688681093}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,747] Trial 72 finished with value: 0.9688507145028884 and parameters: {'n_estimators': 499, 'max_depth': 7, 'learning_rate': 0.38244445432292384, 'gamma': 0.18146664800759046, 'min_child_weight': 2, 'subsample': 0.9596340961165732, 'colsample_bytree': 0.572044864462482, 'reg_alpha': 0.016134020929382414, 'reg_lambda': 0.01234831939559891}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,846] Trial 73 finished with value: 0.9730591871896219 and parameters: {'n_estimators': 604, 'max_depth': 9, 'learning_rate': 0.3523875117331137, 'gamma': 0.5869038873091967, 'min_child_weight': 1, 'subsample': 0.9973259663877005, 'colsample_bytree': 0.6032453080408623, 'reg_alpha': 0.0022034163758147033, 'reg_lambda': 0.003049196789395216}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:45,943] Trial 74 finished with value: 0.9726867335562988 and parameters: {'n_estimators': 643, 'max_depth': 10, 'learning_rate': 0.3115429292430983, 'gamma': 0.036960550625807345, 'min_child_weight': 1, 'subsample': 0.9228507492640425, 'colsample_bytree': 0.5847404975899988, 'reg_alpha': 0.0014779764401295955, 'reg_lambda': 0.003412426872991884}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:46,042] Trial 75 finished with value: 0.9674419783115435 and parameters: {'n_estimators': 736, 'max_depth': 6, 'learning_rate': 0.31250026585052976, 'gamma': 0.00702536125685206, 'min_child_weight': 1, 'subsample': 0.9354922617992198, 'colsample_bytree': 0.5904428924919242, 'reg_alpha': 0.00019799922342255818, 'reg_lambda': 0.002649876404494166}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:46,140] Trial 76 finished with value: 0.96846305868045 and parameters: {'n_estimators': 662, 'max_depth': 10, 'learning_rate': 0.3376390484742646, 'gamma': 0.17746602873003298, 'min_child_weight': 1, 'subsample': 0.9210632567481764, 'colsample_bytree': 0.531169103386247, 'reg_alpha': 5.299213937151595e-05, 'reg_lambda': 0.0003542587698556304}. Best is trial 39 with value: 0.9733835005574136.\n", - "[I 2025-08-18 23:04:46,242] Trial 77 finished with value: 0.9755472788081484 and parameters: {'n_estimators': 699, 'max_depth': 8, 'learning_rate': 0.3024552441518453, 'gamma': 0.031847215034954184, 'min_child_weight': 1, 'subsample': 0.9453725012935073, 'colsample_bytree': 0.5761387875938053, 'reg_alpha': 0.002617366611378274, 'reg_lambda': 0.0010349784161099026}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,342] Trial 78 finished with value: 0.9712754636667679 and parameters: {'n_estimators': 710, 'max_depth': 16, 'learning_rate': 0.2782864761065816, 'gamma': 0.025218929923798795, 'min_child_weight': 1, 'subsample': 0.9452026017018716, 'colsample_bytree': 0.5742454517084862, 'reg_alpha': 0.0007904896535609112, 'reg_lambda': 0.0010678161736113964}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,439] Trial 79 finished with value: 0.9720355731225296 and parameters: {'n_estimators': 705, 'max_depth': 8, 'learning_rate': 0.24162738268963288, 'gamma': 0.03242084611379141, 'min_child_weight': 1, 'subsample': 0.9990849392959138, 'colsample_bytree': 0.5707898574308613, 'reg_alpha': 0.0007599244448927335, 'reg_lambda': 0.000865693881036213}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,540] Trial 80 finished with value: 0.9663651565825478 and parameters: {'n_estimators': 715, 'max_depth': 8, 'learning_rate': 0.2321298214642324, 'gamma': 0.03022699849641668, 'min_child_weight': 1, 'subsample': 0.9755760553478194, 'colsample_bytree': 0.5183018267013588, 'reg_alpha': 7.536762919465367e-06, 'reg_lambda': 0.0008972684138130091}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,634] Trial 81 finished with value: 0.9711842505320767 and parameters: {'n_estimators': 611, 'max_depth': 6, 'learning_rate': 0.202585095609433, 'gamma': 0.015614516083160477, 'min_child_weight': 1, 'subsample': 0.9438468399025172, 'colsample_bytree': 0.5749914104204584, 'reg_alpha': 0.0007169577786597087, 'reg_lambda': 0.003665927983254753}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,722] Trial 82 finished with value: 0.9691876963616094 and parameters: {'n_estimators': 609, 'max_depth': 6, 'learning_rate': 0.1869983439603146, 'gamma': 0.017565215748102506, 'min_child_weight': 1, 'subsample': 0.9986384186074727, 'colsample_bytree': 0.5694324397593564, 'reg_alpha': 0.0018715550848706019, 'reg_lambda': 0.0038007089962539624}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,829] Trial 83 finished with value: 0.9702011756359583 and parameters: {'n_estimators': 690, 'max_depth': 5, 'learning_rate': 0.15378234192456952, 'gamma': 0.026585421213008446, 'min_child_weight': 1, 'subsample': 0.9471578642997183, 'colsample_bytree': 0.5770861818398159, 'reg_alpha': 0.00014343058886510785, 'reg_lambda': 0.0015367425711003662}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:46,921] Trial 84 finished with value: 0.9754687341643864 and parameters: {'n_estimators': 639, 'max_depth': 4, 'learning_rate': 0.2487735126244442, 'gamma': 0.013668381092022869, 'min_child_weight': 1, 'subsample': 0.9738876470197214, 'colsample_bytree': 0.5393776820447042, 'reg_alpha': 6.061029273544998e-05, 'reg_lambda': 0.0020237631280064475}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:47,010] Trial 85 finished with value: 0.9716479173000911 and parameters: {'n_estimators': 648, 'max_depth': 3, 'learning_rate': 0.25369031622209937, 'gamma': 0.011189099120964408, 'min_child_weight': 1, 'subsample': 0.9618607275528647, 'colsample_bytree': 0.5403278959911854, 'reg_alpha': 6.770838783028626e-05, 'reg_lambda': 0.004437258057055608}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:47,109] Trial 86 finished with value: 0.969990878686531 and parameters: {'n_estimators': 765, 'max_depth': 2, 'learning_rate': 0.24109962829948212, 'gamma': 0.010123695604080735, 'min_child_weight': 1, 'subsample': 0.9745058224401574, 'colsample_bytree': 0.5299920014608653, 'reg_alpha': 3.632267987330727e-05, 'reg_lambda': 0.009842578847590693}. Best is trial 77 with value: 0.9755472788081484.\n", - "[I 2025-08-18 23:04:47,206] Trial 87 finished with value: 0.9775793047532177 and parameters: {'n_estimators': 636, 'max_depth': 3, 'learning_rate': 0.28911459468011935, 'gamma': 0.0026877179567177173, 'min_child_weight': 1, 'subsample': 0.9884898945689472, 'colsample_bytree': 0.5529899112143574, 'reg_alpha': 8.780578569353003e-06, 'reg_lambda': 0.024175358439225716}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,291] Trial 88 finished with value: 0.9618374379243946 and parameters: {'n_estimators': 630, 'max_depth': 3, 'learning_rate': 0.3030644325616155, 'gamma': 0.0014905115676082498, 'min_child_weight': 7, 'subsample': 0.9611256405654685, 'colsample_bytree': 0.5008769080768224, 'reg_alpha': 8.389249095912817e-07, 'reg_lambda': 0.025573250031303514}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,384] Trial 89 finished with value: 0.9702391811087464 and parameters: {'n_estimators': 648, 'max_depth': 2, 'learning_rate': 0.24974925657004052, 'gamma': 0.005400230740828263, 'min_child_weight': 2, 'subsample': 0.98727769647163, 'colsample_bytree': 0.542979554752891, 'reg_alpha': 6.773579449524946e-05, 'reg_lambda': 0.13938797071958295}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,484] Trial 90 finished with value: 0.9713134691395562 and parameters: {'n_estimators': 678, 'max_depth': 4, 'learning_rate': 0.27329622005890974, 'gamma': 0.0025640663065522483, 'min_child_weight': 1, 'subsample': 0.9685762941440739, 'colsample_bytree': 0.5533183680424663, 'reg_alpha': 9.554742944191967e-06, 'reg_lambda': 0.05646506170705333}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,600] Trial 91 finished with value: 0.9720735785953177 and parameters: {'n_estimators': 685, 'max_depth': 4, 'learning_rate': 0.27964910528085046, 'gamma': 0.002726438477417822, 'min_child_weight': 1, 'subsample': 0.9999643990452035, 'colsample_bytree': 0.5523292566223091, 'reg_alpha': 1.3960839467745119e-05, 'reg_lambda': 0.01415347048036145}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,692] Trial 92 finished with value: 0.9752204317421709 and parameters: {'n_estimators': 593, 'max_depth': 4, 'learning_rate': 0.32272873880627245, 'gamma': 0.0003076681496953475, 'min_child_weight': 1, 'subsample': 0.9988143324319202, 'colsample_bytree': 0.5182298233134042, 'reg_alpha': 4.764947763017983e-06, 'reg_lambda': 0.012883267517371262}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,777] Trial 93 finished with value: 0.9702746528833485 and parameters: {'n_estimators': 592, 'max_depth': 4, 'learning_rate': 0.32321683238270205, 'gamma': 0.00023242624645060717, 'min_child_weight': 1, 'subsample': 0.9883656895313044, 'colsample_bytree': 0.5249002470585026, 'reg_alpha': 3.177832241884098e-06, 'reg_lambda': 0.017907514716424745}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,866] Trial 94 finished with value: 0.9754687341643864 and parameters: {'n_estimators': 719, 'max_depth': 5, 'learning_rate': 0.35309665196705153, 'gamma': 0.0012381542386533933, 'min_child_weight': 2, 'subsample': 0.9938001959815986, 'colsample_bytree': 0.5135263406023138, 'reg_alpha': 2.140299584024884e-05, 'reg_lambda': 0.010354897273928652}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:47,964] Trial 95 finished with value: 0.9702619843924193 and parameters: {'n_estimators': 813, 'max_depth': 4, 'learning_rate': 0.35202078039521256, 'gamma': 0.0008558118176606106, 'min_child_weight': 2, 'subsample': 0.9786791914929385, 'colsample_bytree': 0.5169883732201127, 'reg_alpha': 4.819331670670429e-06, 'reg_lambda': 0.01225335075642242}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,050] Trial 96 finished with value: 0.9659420289855072 and parameters: {'n_estimators': 549, 'max_depth': 5, 'learning_rate': 0.30573045471770227, 'gamma': 0.0006382196831107483, 'min_child_weight': 2, 'subsample': 0.9975854577557746, 'colsample_bytree': 0.5149033410261374, 'reg_alpha': 1.7285610267319068e-05, 'reg_lambda': 0.04954756540940724}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,140] Trial 97 finished with value: 0.9701733049559136 and parameters: {'n_estimators': 726, 'max_depth': 2, 'learning_rate': 0.2877388004810307, 'gamma': 0.0003280781904783974, 'min_child_weight': 1, 'subsample': 0.9563657324404314, 'colsample_bytree': 0.5071027752196428, 'reg_alpha': 1.6962797991959727e-05, 'reg_lambda': 0.00907410879093517}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,228] Trial 98 finished with value: 0.9579279416235937 and parameters: {'n_estimators': 753, 'max_depth': 1, 'learning_rate': 0.34676644343134116, 'gamma': 0.0012565205080685606, 'min_child_weight': 2, 'subsample': 0.9724664289612212, 'colsample_bytree': 0.5608401123520345, 'reg_alpha': 1.398799276624877e-06, 'reg_lambda': 0.15340330599489194}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,317] Trial 99 finished with value: 0.9712729299685823 and parameters: {'n_estimators': 628, 'max_depth': 3, 'learning_rate': 0.3685623760852724, 'gamma': 0.00016314010705137475, 'min_child_weight': 1, 'subsample': 0.9018849176689584, 'colsample_bytree': 0.5526193503254366, 'reg_alpha': 3.4172598118958266e-06, 'reg_lambda': 0.35726720012149144}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,408] Trial 100 finished with value: 0.9684123847167324 and parameters: {'n_estimators': 685, 'max_depth': 5, 'learning_rate': 0.32205265663271354, 'gamma': 0.0003733394372953507, 'min_child_weight': 2, 'subsample': 0.9269329238786695, 'colsample_bytree': 0.5328390047076582, 'reg_alpha': 6.468453572696246e-06, 'reg_lambda': 0.0247247964033616}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,492] Trial 101 finished with value: 0.9734341745211312 and parameters: {'n_estimators': 657, 'max_depth': 4, 'learning_rate': 0.2902610534781817, 'gamma': 0.003144326892729591, 'min_child_weight': 1, 'subsample': 0.9994520720533928, 'colsample_bytree': 0.5979372134689044, 'reg_alpha': 2.811792565093441e-05, 'reg_lambda': 0.0024288390385784997}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,590] Trial 102 finished with value: 0.9678017634539373 and parameters: {'n_estimators': 794, 'max_depth': 4, 'learning_rate': 0.29965776922838716, 'gamma': 0.003105619445624373, 'min_child_weight': 1, 'subsample': 0.9811178081384474, 'colsample_bytree': 0.5970710263821791, 'reg_alpha': 3.448408606278336e-05, 'reg_lambda': 0.0025213111005363957}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,680] Trial 103 finished with value: 0.9684681260768218 and parameters: {'n_estimators': 663, 'max_depth': 4, 'learning_rate': 0.26839935650628705, 'gamma': 0.0005156188710353528, 'min_child_weight': 1, 'subsample': 0.9892553837421945, 'colsample_bytree': 0.5402218509766766, 'reg_alpha': 1.2238097567923076e-05, 'reg_lambda': 0.013305019890137302}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,768] Trial 104 finished with value: 0.9755194081281037 and parameters: {'n_estimators': 560, 'max_depth': 3, 'learning_rate': 0.28236255406126465, 'gamma': 0.004741677790575585, 'min_child_weight': 1, 'subsample': 0.9531167819448579, 'colsample_bytree': 0.5099770858154159, 'reg_alpha': 2.984910631985938e-05, 'reg_lambda': 0.007518398425430544}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,857] Trial 105 finished with value: 0.9730085132259045 and parameters: {'n_estimators': 596, 'max_depth': 2, 'learning_rate': 0.3222004116025429, 'gamma': 0.004489752812161376, 'min_child_weight': 1, 'subsample': 0.9352956487444385, 'colsample_bytree': 0.5865015029021471, 'reg_alpha': 2.7008940823248416e-05, 'reg_lambda': 0.007828445330780436}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:48,937] Trial 106 finished with value: 0.9669631093544137 and parameters: {'n_estimators': 595, 'max_depth': 2, 'learning_rate': 0.3267714012542968, 'gamma': 0.0016705946716529846, 'min_child_weight': 1, 'subsample': 0.9536853948914599, 'colsample_bytree': 0.5893227042142406, 'reg_alpha': 2.1190401208330304e-05, 'reg_lambda': 0.0063492970335785335}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,012] Trial 107 finished with value: 0.9649944258639911 and parameters: {'n_estimators': 551, 'max_depth': 1, 'learning_rate': 0.3576194826916017, 'gamma': 0.004801886110733527, 'min_child_weight': 6, 'subsample': 0.9338819770386118, 'colsample_bytree': 0.6214947240444341, 'reg_alpha': 2.8234266675465392e-05, 'reg_lambda': 0.008051822527829319}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,099] Trial 108 finished with value: 0.9720609101043882 and parameters: {'n_estimators': 595, 'max_depth': 3, 'learning_rate': 0.31458876017437437, 'gamma': 0.008358899230048938, 'min_child_weight': 1, 'subsample': 0.968750010105244, 'colsample_bytree': 0.6043042278252939, 'reg_alpha': 2.393229312399412e-06, 'reg_lambda': 0.0021086902788013838}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,176] Trial 109 finished with value: 0.9595520421607379 and parameters: {'n_estimators': 564, 'max_depth': 3, 'learning_rate': 0.29332591763899823, 'gamma': 0.002008519656446403, 'min_child_weight': 10, 'subsample': 0.9178749512403971, 'colsample_bytree': 0.5624548512353742, 'reg_alpha': 6.279674953618662e-05, 'reg_lambda': 0.03769905974473238}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,256] Trial 110 finished with value: 0.9681640822945171 and parameters: {'n_estimators': 627, 'max_depth': 2, 'learning_rate': 0.21619927350223261, 'gamma': 0.0009373960888666258, 'min_child_weight': 2, 'subsample': 0.6307794924226682, 'colsample_bytree': 0.5836006154710169, 'reg_alpha': 2.713808381396758e-07, 'reg_lambda': 0.0050776218812680785}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,342] Trial 111 finished with value: 0.9708346001824262 and parameters: {'n_estimators': 651, 'max_depth': 5, 'learning_rate': 0.40366773427286373, 'gamma': 0.005707361249345923, 'min_child_weight': 1, 'subsample': 0.9799469111616341, 'colsample_bytree': 0.5116600324384395, 'reg_alpha': 8.85253713948703e-06, 'reg_lambda': 0.003065231130945774}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,432] Trial 112 finished with value: 0.9736951454342758 and parameters: {'n_estimators': 583, 'max_depth': 3, 'learning_rate': 0.37574148917155586, 'gamma': 0.0009319568992135199, 'min_child_weight': 1, 'subsample': 0.9397410388904857, 'colsample_bytree': 0.5235594910355523, 'reg_alpha': 4.017162866775182e-05, 'reg_lambda': 0.018251272759087948}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,520] Trial 113 finished with value: 0.973771156379852 and parameters: {'n_estimators': 578, 'max_depth': 3, 'learning_rate': 0.380812899535783, 'gamma': 0.0011512223457226971, 'min_child_weight': 1, 'subsample': 0.9388546288873797, 'colsample_bytree': 0.5352536425774438, 'reg_alpha': 9.09130166376462e-05, 'reg_lambda': 0.018725988923139904}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,598] Trial 114 finished with value: 0.9737838248707813 and parameters: {'n_estimators': 530, 'max_depth': 3, 'learning_rate': 0.3742761757944042, 'gamma': 0.0029273154938769808, 'min_child_weight': 1, 'subsample': 0.9529626320951139, 'colsample_bytree': 0.5232564805201162, 'reg_alpha': 9.104169023548576e-05, 'reg_lambda': 0.01996768613708404}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,681] Trial 115 finished with value: 0.9756460930373974 and parameters: {'n_estimators': 533, 'max_depth': 3, 'learning_rate': 0.3787657790858809, 'gamma': 0.0011307839139740017, 'min_child_weight': 1, 'subsample': 0.9535686443026108, 'colsample_bytree': 0.5245456491257551, 'reg_alpha': 0.00013522790859490737, 'reg_lambda': 0.019711799698721878}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,755] Trial 116 finished with value: 0.9635198135198134 and parameters: {'n_estimators': 485, 'max_depth': 3, 'learning_rate': 0.38091477840580124, 'gamma': 0.0009720468741725009, 'min_child_weight': 2, 'subsample': 0.8986807103789741, 'colsample_bytree': 0.5273155593064995, 'reg_alpha': 0.00013848719337144623, 'reg_lambda': 0.08091061668198583}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,834] Trial 117 finished with value: 0.9717289956420393 and parameters: {'n_estimators': 527, 'max_depth': 4, 'learning_rate': 0.4076052802456525, 'gamma': 0.0004831402272338826, 'min_child_weight': 1, 'subsample': 0.9533851366158632, 'colsample_bytree': 0.5220037354837226, 'reg_alpha': 4.5139430500113255e-05, 'reg_lambda': 0.02575574317660115}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:49,924] Trial 118 finished with value: 0.9752331002331003 and parameters: {'n_estimators': 563, 'max_depth': 3, 'learning_rate': 0.369521549644023, 'gamma': 0.0033558215982748703, 'min_child_weight': 1, 'subsample': 0.9667985061852574, 'colsample_bytree': 0.5372400830436947, 'reg_alpha': 9.504911886451962e-05, 'reg_lambda': 0.018904666487589226}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,013] Trial 119 finished with value: 0.9705736292692814 and parameters: {'n_estimators': 563, 'max_depth': 4, 'learning_rate': 0.4299915817303335, 'gamma': 0.001525288316607799, 'min_child_weight': 1, 'subsample': 0.9689561356982478, 'colsample_bytree': 0.5359613906712454, 'reg_alpha': 8.351303475967823e-05, 'reg_lambda': 0.018419935953742344}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,090] Trial 120 finished with value: 0.9639074693422518 and parameters: {'n_estimators': 451, 'max_depth': 3, 'learning_rate': 0.3667210874551086, 'gamma': 0.0021214031984273544, 'min_child_weight': 2, 'subsample': 0.9432651878904321, 'colsample_bytree': 0.5014124944408871, 'reg_alpha': 0.0003167811707490163, 'reg_lambda': 0.04607793156075455}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,171] Trial 121 finished with value: 0.9724004256612953 and parameters: {'n_estimators': 580, 'max_depth': 3, 'learning_rate': 0.38856872366310524, 'gamma': 0.0007746428169296834, 'min_child_weight': 1, 'subsample': 0.9623910956260555, 'colsample_bytree': 0.5119448445892998, 'reg_alpha': 0.0001022046692298684, 'reg_lambda': 0.01876632074345833}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,249] Trial 122 finished with value: 0.9663018141279013 and parameters: {'n_estimators': 523, 'max_depth': 5, 'learning_rate': 0.34228646898366927, 'gamma': 0.004028194445590085, 'min_child_weight': 1, 'subsample': 0.9828478575776481, 'colsample_bytree': 0.5450122834491693, 'reg_alpha': 4.336905329638909e-05, 'reg_lambda': 0.07311566300587641}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,326] Trial 123 finished with value: 0.9660028377419682 and parameters: {'n_estimators': 543, 'max_depth': 2, 'learning_rate': 0.3710652116662308, 'gamma': 0.003426110492596931, 'min_child_weight': 1, 'subsample': 0.9519074894178458, 'colsample_bytree': 0.52062981297652, 'reg_alpha': 0.00019606561378930507, 'reg_lambda': 0.00010956050738603163}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,402] Trial 124 finished with value: 0.9675078544643763 and parameters: {'n_estimators': 490, 'max_depth': 3, 'learning_rate': 0.3419021639421203, 'gamma': 0.001379753702423482, 'min_child_weight': 1, 'subsample': 0.5402074886692497, 'colsample_bytree': 0.534963564474138, 'reg_alpha': 2.4804707361280354e-05, 'reg_lambda': 0.02366181477486779}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,492] Trial 125 finished with value: 0.9664031620553359 and parameters: {'n_estimators': 623, 'max_depth': 4, 'learning_rate': 0.2584426107557688, 'gamma': 0.0002969583549970284, 'min_child_weight': 1, 'subsample': 0.8659075091283825, 'colsample_bytree': 0.5477391905798454, 'reg_alpha': 6.0849397689869715e-06, 'reg_lambda': 0.03055499300789043}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,569] Trial 126 finished with value: 0.9709739535826492 and parameters: {'n_estimators': 564, 'max_depth': 3, 'learning_rate': 0.3607708090917786, 'gamma': 0.007904872146312887, 'min_child_weight': 1, 'subsample': 0.9732660624180509, 'colsample_bytree': 0.5596402152998722, 'reg_alpha': 0.0001532572414280914, 'reg_lambda': 0.1245305580605709}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,660] Trial 127 finished with value: 0.9620680044593088 and parameters: {'n_estimators': 507, 'max_depth': 6, 'learning_rate': 0.40969970909179665, 'gamma': 0.002569636211762046, 'min_child_weight': 2, 'subsample': 0.8829928862860841, 'colsample_bytree': 0.5098754820895927, 'reg_alpha': 1.3035647256514827e-05, 'reg_lambda': 0.010289122123771933}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,736] Trial 128 finished with value: 0.9603476233911017 and parameters: {'n_estimators': 577, 'max_depth': 1, 'learning_rate': 0.39060663548307156, 'gamma': 0.0010891361828261408, 'min_child_weight': 1, 'subsample': 0.9379188131627437, 'colsample_bytree': 0.524948913298735, 'reg_alpha': 8.586777823699555e-05, 'reg_lambda': 0.04302715195504146}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,817] Trial 129 finished with value: 0.9663702239789196 and parameters: {'n_estimators': 546, 'max_depth': 2, 'learning_rate': 0.3340394526859328, 'gamma': 0.005928493392740887, 'min_child_weight': 1, 'subsample': 0.9854164381951216, 'colsample_bytree': 0.5401827154061658, 'reg_alpha': 3.574390952002835e-05, 'reg_lambda': 0.01684875458666302}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,905] Trial 130 finished with value: 0.9653162055335969 and parameters: {'n_estimators': 616, 'max_depth': 4, 'learning_rate': 0.28549506379050643, 'gamma': 1.2263018757725954e-07, 'min_child_weight': 2, 'subsample': 0.959035504220871, 'colsample_bytree': 0.5004808635645343, 'reg_alpha': 6.108068069373782e-05, 'reg_lambda': 4.081789431923016e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:50,995] Trial 131 finished with value: 0.974407114624506 and parameters: {'n_estimators': 607, 'max_depth': 5, 'learning_rate': 0.355606899809378, 'gamma': 0.0016875775407594427, 'min_child_weight': 1, 'subsample': 0.9899274318285423, 'colsample_bytree': 0.522467631554332, 'reg_alpha': 1.9439920919411324e-05, 'reg_lambda': 0.005478042686972311}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,083] Trial 132 finished with value: 0.9697349751697578 and parameters: {'n_estimators': 659, 'max_depth': 5, 'learning_rate': 0.3758099733710491, 'gamma': 0.0020911550697864313, 'min_child_weight': 1, 'subsample': 0.9896734709877024, 'colsample_bytree': 0.5200962421716877, 'reg_alpha': 1.0531070308464693e-05, 'reg_lambda': 0.006260553029093111}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,160] Trial 133 finished with value: 0.9691623593797507 and parameters: {'n_estimators': 579, 'max_depth': 4, 'learning_rate': 0.3543435466787781, 'gamma': 0.003457287339258925, 'min_child_weight': 1, 'subsample': 0.9699357364188769, 'colsample_bytree': 0.5319377512135547, 'reg_alpha': 1.6344689723836534e-05, 'reg_lambda': 0.011513426714595142}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,249] Trial 134 finished with value: 0.9685137326441675 and parameters: {'n_estimators': 609, 'max_depth': 3, 'learning_rate': 0.29969094509558114, 'gamma': 0.0006201750540023973, 'min_child_weight': 1, 'subsample': 0.9465508766827356, 'colsample_bytree': 0.549628779727799, 'reg_alpha': 0.00023383467565098683, 'reg_lambda': 0.00473897887352641}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,340] Trial 135 finished with value: 0.9702113104287017 and parameters: {'n_estimators': 702, 'max_depth': 5, 'learning_rate': 0.39838626436610647, 'gamma': 0.013457480792657921, 'min_child_weight': 1, 'subsample': 0.9284918315242744, 'colsample_bytree': 0.5111760740688991, 'reg_alpha': 2.112013867824408e-05, 'reg_lambda': 0.0016412145138216558}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,416] Trial 136 finished with value: 0.9590706395054222 and parameters: {'n_estimators': 423, 'max_depth': 3, 'learning_rate': 0.42953000397831703, 'gamma': 0.0017375341373862645, 'min_child_weight': 9, 'subsample': 0.9781959850635785, 'colsample_bytree': 0.8378674178811536, 'reg_alpha': 9.858181986503538e-05, 'reg_lambda': 0.0322880013964512}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,504] Trial 137 finished with value: 0.973811695550826 and parameters: {'n_estimators': 728, 'max_depth': 4, 'learning_rate': 0.3342825551208779, 'gamma': 0.0013440099679389622, 'min_child_weight': 1, 'subsample': 0.9916941709687607, 'colsample_bytree': 0.5655061047088268, 'reg_alpha': 5.070174259490981e-05, 'reg_lambda': 0.05985267611255229}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,604] Trial 138 finished with value: 0.9692383703253269 and parameters: {'n_estimators': 749, 'max_depth': 4, 'learning_rate': 0.32844184046054403, 'gamma': 0.0010007539710985736, 'min_child_weight': 5, 'subsample': 0.9920762896755643, 'colsample_bytree': 0.565157003127687, 'reg_alpha': 4.908631252458206e-05, 'reg_lambda': 0.0959049021065359}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,694] Trial 139 finished with value: 0.9708852741461437 and parameters: {'n_estimators': 673, 'max_depth': 5, 'learning_rate': 0.3774025399941191, 'gamma': 0.000643044874536142, 'min_child_weight': 1, 'subsample': 0.9651415410028824, 'colsample_bytree': 0.5256854732827111, 'reg_alpha': 4.714024807154563e-06, 'reg_lambda': 0.9912937619442326}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,783] Trial 140 finished with value: 0.9634792743488395 and parameters: {'n_estimators': 717, 'max_depth': 2, 'learning_rate': 0.3137203687154433, 'gamma': 0.0003873298406166423, 'min_child_weight': 1, 'subsample': 0.9913943483341556, 'colsample_bytree': 0.5377420413971642, 'reg_alpha': 3.32220834872906e-05, 'reg_lambda': 0.056686545270045595}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,872] Trial 141 finished with value: 0.9681032735380561 and parameters: {'n_estimators': 732, 'max_depth': 4, 'learning_rate': 0.3457977422562131, 'gamma': 0.002976971721662494, 'min_child_weight': 1, 'subsample': 0.9763124432392175, 'colsample_bytree': 0.5543880729679166, 'reg_alpha': 7.545227219322496e-05, 'reg_lambda': 0.009449314626667723}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:51,962] Trial 142 finished with value: 0.9723598864903213 and parameters: {'n_estimators': 632, 'max_depth': 3, 'learning_rate': 0.275963901659525, 'gamma': 0.0016243745622636782, 'min_child_weight': 1, 'subsample': 0.9530092292388275, 'colsample_bytree': 0.5175852195916012, 'reg_alpha': 0.0001427649603465201, 'reg_lambda': 0.0005683368270736766}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,051] Trial 143 finished with value: 0.9677688253775212 and parameters: {'n_estimators': 592, 'max_depth': 6, 'learning_rate': 0.3336579888058368, 'gamma': 0.00014631390669258675, 'min_child_weight': 1, 'subsample': 0.9999417063182031, 'colsample_bytree': 0.9335216594524222, 'reg_alpha': 4.6191952330179104e-05, 'reg_lambda': 0.016752760821593927}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,141] Trial 144 finished with value: 0.9641684402553968 and parameters: {'n_estimators': 529, 'max_depth': 4, 'learning_rate': 0.36114155417739013, 'gamma': 0.0013312075417919174, 'min_child_weight': 1, 'subsample': 0.9623533998092761, 'colsample_bytree': 0.5302807739145121, 'reg_alpha': 1.9198762008560404e-06, 'reg_lambda': 0.02423055657998778}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,232] Trial 145 finished with value: 0.9663144826188306 and parameters: {'n_estimators': 696, 'max_depth': 3, 'learning_rate': 0.29694209248501263, 'gamma': 0.006637136428949488, 'min_child_weight': 2, 'subsample': 0.9832551742092744, 'colsample_bytree': 0.5451968446750411, 'reg_alpha': 2.3355865575390215e-05, 'reg_lambda': 6.480226641591573e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,323] Trial 146 finished with value: 0.9722458700719571 and parameters: {'n_estimators': 772, 'max_depth': 2, 'learning_rate': 0.3119949296748683, 'gamma': 0.004385003172565624, 'min_child_weight': 1, 'subsample': 0.911161698166705, 'colsample_bytree': 0.5674565521458058, 'reg_alpha': 8.339882112703323e-06, 'reg_lambda': 0.22744493185559642}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,414] Trial 147 finished with value: 0.9705989662511403 and parameters: {'n_estimators': 649, 'max_depth': 5, 'learning_rate': 0.3886513667571667, 'gamma': 0.0023992741913581236, 'min_child_weight': 1, 'subsample': 0.9412909731446526, 'colsample_bytree': 0.5082665367483681, 'reg_alpha': 1.3917011685173996e-05, 'reg_lambda': 0.004983404179282378}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,505] Trial 148 finished with value: 0.9641785750481404 and parameters: {'n_estimators': 559, 'max_depth': 7, 'learning_rate': 0.2656435390958021, 'gamma': 0.010482805664855063, 'min_child_weight': 1, 'subsample': 0.9700690013382033, 'colsample_bytree': 0.553896550744323, 'reg_alpha': 2.703827604890988e-05, 'reg_lambda': 0.008979484259118622}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,595] Trial 149 finished with value: 0.9656785243741766 and parameters: {'n_estimators': 675, 'max_depth': 4, 'learning_rate': 0.3481169895361487, 'gamma': 0.0190297439645008, 'min_child_weight': 1, 'subsample': 0.9886286410235502, 'colsample_bytree': 0.5248371166735615, 'reg_alpha': 0.00011080258805194705, 'reg_lambda': 0.013823520690237876}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,686] Trial 150 finished with value: 0.971652984696463 and parameters: {'n_estimators': 610, 'max_depth': 3, 'learning_rate': 0.3647380803471352, 'gamma': 0.0007750215340674814, 'min_child_weight': 2, 'subsample': 0.9544048764946547, 'colsample_bytree': 0.578212060417031, 'reg_alpha': 0.0003801255473377791, 'reg_lambda': 0.03725850213457456}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,776] Trial 151 finished with value: 0.9720229046316003 and parameters: {'n_estimators': 592, 'max_depth': 9, 'learning_rate': 0.3464425517062153, 'gamma': 0.0012319969445261018, 'min_child_weight': 1, 'subsample': 0.9985073180656334, 'colsample_bytree': 0.5974960617683841, 'reg_alpha': 5.515700111193299e-05, 'reg_lambda': 0.0033159882823894545}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,865] Trial 152 finished with value: 0.9688507145028884 and parameters: {'n_estimators': 540, 'max_depth': 4, 'learning_rate': 0.38017768085764003, 'gamma': 0.002973199513913439, 'min_child_weight': 1, 'subsample': 0.9799912178341434, 'colsample_bytree': 0.5404784885391826, 'reg_alpha': 3.899089387434627e-05, 'reg_lambda': 0.0015310715824011964}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:52,954] Trial 153 finished with value: 0.9699376710246275 and parameters: {'n_estimators': 638, 'max_depth': 3, 'learning_rate': 0.3293247587583182, 'gamma': 1.080918771118752e-08, 'min_child_weight': 1, 'subsample': 0.9748569594260413, 'colsample_bytree': 0.5627494059605304, 'reg_alpha': 0.0001868642563379178, 'reg_lambda': 0.00610063335717874}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,045] Trial 154 finished with value: 0.9727247390290866 and parameters: {'n_estimators': 579, 'max_depth': 8, 'learning_rate': 0.3590865853470216, 'gamma': 0.00023242766577177755, 'min_child_weight': 1, 'subsample': 0.9961763419959316, 'colsample_bytree': 0.5001855233864979, 'reg_alpha': 4.938473306881137e-06, 'reg_lambda': 0.05945419728506628}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,132] Trial 155 finished with value: 0.9698236546062633 and parameters: {'n_estimators': 511, 'max_depth': 2, 'learning_rate': 0.23177088731265877, 'gamma': 0.00220051619789768, 'min_child_weight': 1, 'subsample': 0.9617219946146195, 'colsample_bytree': 0.5155296562213243, 'reg_alpha': 0.41356358892481515, 'reg_lambda': 0.0021647051888757846}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,221] Trial 156 finished with value: 0.9642849903719469 and parameters: {'n_estimators': 608, 'max_depth': 4, 'learning_rate': 0.310179089365562, 'gamma': 0.0004899069210826855, 'min_child_weight': 1, 'subsample': 0.989151895567528, 'colsample_bytree': 0.6155162461276559, 'reg_alpha': 7.038828394482472e-05, 'reg_lambda': 0.018486913379264905}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,306] Trial 157 finished with value: 0.968800040539171 and parameters: {'n_estimators': 625, 'max_depth': 3, 'learning_rate': 0.28337124920511253, 'gamma': 0.005312986290264966, 'min_child_weight': 1, 'subsample': 0.9471200013006852, 'colsample_bytree': 0.5371368095603188, 'reg_alpha': 2.126502030369528e-05, 'reg_lambda': 0.007672507188909957}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,396] Trial 158 finished with value: 0.9688127090301004 and parameters: {'n_estimators': 560, 'max_depth': 5, 'learning_rate': 0.24864922427836095, 'gamma': 0.001724231530528261, 'min_child_weight': 1, 'subsample': 0.9275859919551936, 'colsample_bytree': 0.5485555398820796, 'reg_alpha': 0.22167735775120456, 'reg_lambda': 0.012725979226750948}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,472] Trial 159 finished with value: 0.9690990169251039 and parameters: {'n_estimators': 466, 'max_depth': 7, 'learning_rate': 0.4138830978222457, 'gamma': 0.008325545281432306, 'min_child_weight': 2, 'subsample': 0.9825726014682536, 'colsample_bytree': 0.5288970024992221, 'reg_alpha': 1.1950616323811105e-05, 'reg_lambda': 0.004148040954584921}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,575] Trial 160 finished with value: 0.9681007398398702 and parameters: {'n_estimators': 665, 'max_depth': 2, 'learning_rate': 0.10656692051303243, 'gamma': 0.0034721265000381826, 'min_child_weight': 1, 'subsample': 0.6041603502459372, 'colsample_bytree': 0.8973681381628347, 'reg_alpha': 8.155092256320305e-07, 'reg_lambda': 0.0026912192428167675}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,653] Trial 161 finished with value: 0.9741334752204317 and parameters: {'n_estimators': 593, 'max_depth': 2, 'learning_rate': 0.3316977172429725, 'gamma': 0.00442101924584059, 'min_child_weight': 1, 'subsample': 0.9383014449372667, 'colsample_bytree': 0.583117916065411, 'reg_alpha': 3.380931076086002e-05, 'reg_lambda': 0.008524632802382586}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,731] Trial 162 finished with value: 0.9709106111280026 and parameters: {'n_estimators': 592, 'max_depth': 3, 'learning_rate': 0.3361791828373549, 'gamma': 0.000985104918156739, 'min_child_weight': 1, 'subsample': 0.9689753750776854, 'colsample_bytree': 0.582026572904053, 'reg_alpha': 2.9623097239471037e-05, 'reg_lambda': 0.023865897227663392}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,818] Trial 163 finished with value: 0.972364953886693 and parameters: {'n_estimators': 544, 'max_depth': 2, 'learning_rate': 0.36753628914761743, 'gamma': 0.003867620019904887, 'min_child_weight': 1, 'subsample': 0.9163941822885812, 'colsample_bytree': 0.5934172796052541, 'reg_alpha': 1.6872233434997325e-05, 'reg_lambda': 0.0012256804410906703}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,909] Trial 164 finished with value: 0.9649538866930174 and parameters: {'n_estimators': 644, 'max_depth': 4, 'learning_rate': 0.3217185820552294, 'gamma': 0.9074683779076849, 'min_child_weight': 1, 'subsample': 0.9404194835151828, 'colsample_bytree': 0.5716382974503587, 'reg_alpha': 4.5156868287806393e-05, 'reg_lambda': 0.009577284570238343}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:53,989] Trial 165 finished with value: 0.9582623897841289 and parameters: {'n_estimators': 572, 'max_depth': 1, 'learning_rate': 0.35434018519246835, 'gamma': 0.006054890244988751, 'min_child_weight': 1, 'subsample': 0.9565629468808314, 'colsample_bytree': 0.6064348733438767, 'reg_alpha': 0.00011506343284625452, 'reg_lambda': 0.03650487541601268}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,068] Trial 166 finished with value: 0.9660433769129421 and parameters: {'n_estimators': 606, 'max_depth': 3, 'learning_rate': 0.2967811217926221, 'gamma': 0.002177647575750638, 'min_child_weight': 4, 'subsample': 0.998649545486057, 'colsample_bytree': 0.5185902261954761, 'reg_alpha': 8.042129768295383e-05, 'reg_lambda': 0.014443731544619897}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,147] Trial 167 finished with value: 0.9681007398398702 and parameters: {'n_estimators': 690, 'max_depth': 4, 'learning_rate': 0.38997942152940307, 'gamma': 0.0013930912234913896, 'min_child_weight': 1, 'subsample': 0.977585735981025, 'colsample_bytree': 0.5600326728904678, 'reg_alpha': 8.024671426853231e-06, 'reg_lambda': 0.005881071752141783}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,225] Trial 168 finished with value: 0.9663524880916186 and parameters: {'n_estimators': 518, 'max_depth': 9, 'learning_rate': 0.37517946961696524, 'gamma': 0.2884197766559136, 'min_child_weight': 2, 'subsample': 0.9320238547852112, 'colsample_bytree': 0.5116644916138443, 'reg_alpha': 3.510454301920386e-05, 'reg_lambda': 0.00396091516537362}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,303] Trial 169 finished with value: 0.9733835005574136 and parameters: {'n_estimators': 493, 'max_depth': 3, 'learning_rate': 0.323016657794504, 'gamma': 0.0008040858558472051, 'min_child_weight': 1, 'subsample': 0.9650583288653142, 'colsample_bytree': 0.5335385167426343, 'reg_alpha': 0.00025883717994882905, 'reg_lambda': 1.4790057261225227e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,397] Trial 170 finished with value: 0.9701986419377724 and parameters: {'n_estimators': 490, 'max_depth': 3, 'learning_rate': 0.321492205338363, 'gamma': 0.0007229956299063446, 'min_child_weight': 1, 'subsample': 0.9471452120455542, 'colsample_bytree': 0.5341908031859132, 'reg_alpha': 5.7889158157425586e-05, 'reg_lambda': 2.5464473413471723e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,464] Trial 171 finished with value: 0.9694106618019662 and parameters: {'n_estimators': 215, 'max_depth': 2, 'learning_rate': 0.3439161658472922, 'gamma': 0.0011441221668909544, 'min_child_weight': 1, 'subsample': 0.9634326817470634, 'colsample_bytree': 0.5247209277418037, 'reg_alpha': 0.00016940381362453118, 'reg_lambda': 0.02385174376916467}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,555] Trial 172 finished with value: 0.9706167021384413 and parameters: {'n_estimators': 619, 'max_depth': 3, 'learning_rate': 0.3054421107140958, 'gamma': 0.0026032231277366247, 'min_child_weight': 1, 'subsample': 0.9860629143288514, 'colsample_bytree': 0.547967448961253, 'reg_alpha': 0.0002849202968485869, 'reg_lambda': 2.6299709321578504e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,645] Trial 173 finished with value: 0.971946893686024 and parameters: {'n_estimators': 720, 'max_depth': 4, 'learning_rate': 0.33341255577347795, 'gamma': 0.0016105012826958308, 'min_child_weight': 1, 'subsample': 0.9679139315267277, 'colsample_bytree': 0.5386463925647356, 'reg_alpha': 8.43176289243587e-05, 'reg_lambda': 4.340287507851219e-06}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,724] Trial 174 finished with value: 0.9716605857910207 and parameters: {'n_estimators': 557, 'max_depth': 5, 'learning_rate': 0.2901160057271195, 'gamma': 0.00032942746566321543, 'min_child_weight': 1, 'subsample': 0.9765070332415594, 'colsample_bytree': 0.5071537214617675, 'reg_alpha': 0.0004723169262131176, 'reg_lambda': 6.832514561560678e-06}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,805] Trial 175 finished with value: 0.9691116854160333 and parameters: {'n_estimators': 588, 'max_depth': 3, 'learning_rate': 0.3522900041666762, 'gamma': 0.004165093913741628, 'min_child_weight': 1, 'subsample': 0.9999358736000473, 'colsample_bytree': 0.5570975897786812, 'reg_alpha': 0.00011310018708618362, 'reg_lambda': 1.5899845363994675e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,907] Trial 176 finished with value: 0.9701859734468432 and parameters: {'n_estimators': 795, 'max_depth': 3, 'learning_rate': 0.2661263579232849, 'gamma': 0.0005314614635974421, 'min_child_weight': 1, 'subsample': 0.955262002780409, 'colsample_bytree': 0.5218601743864764, 'reg_alpha': 3.278095954186388e-05, 'reg_lambda': 0.007563842393120928}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:54,987] Trial 177 finished with value: 0.9691876963616094 and parameters: {'n_estimators': 528, 'max_depth': 4, 'learning_rate': 0.4052836482941531, 'gamma': 0.0007836995912045476, 'min_child_weight': 1, 'subsample': 0.9835358139883751, 'colsample_bytree': 0.5748069554328435, 'reg_alpha': 1.8927713418645845e-05, 'reg_lambda': 0.016993878052280156}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,078] Trial 178 finished with value: 0.9646042363433669 and parameters: {'n_estimators': 659, 'max_depth': 10, 'learning_rate': 0.3716414273907836, 'gamma': 0.0030133506411139394, 'min_child_weight': 2, 'subsample': 0.9398036029857711, 'colsample_bytree': 0.53143727573368, 'reg_alpha': 0.00023311010825420792, 'reg_lambda': 0.012640641270748694}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,167] Trial 179 finished with value: 0.9698616600790514 and parameters: {'n_estimators': 747, 'max_depth': 2, 'learning_rate': 0.32001440829474825, 'gamma': 0.0019126003149610587, 'min_child_weight': 1, 'subsample': 0.9707912347002509, 'colsample_bytree': 0.5423708785702983, 'reg_alpha': 5.966945807712596e-05, 'reg_lambda': 1.0493234578616303e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,248] Trial 180 finished with value: 0.9551535421100639 and parameters: {'n_estimators': 294, 'max_depth': 1, 'learning_rate': 0.3357416315742316, 'gamma': 0.007657877580656061, 'min_child_weight': 1, 'subsample': 0.9919818138814995, 'colsample_bytree': 0.5887452792406924, 'reg_alpha': 4.579238829952115e-05, 'reg_lambda': 0.0018385729955730126}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,341] Trial 181 finished with value: 0.9701226309921962 and parameters: {'n_estimators': 595, 'max_depth': 2, 'learning_rate': 0.3196711674185751, 'gamma': 0.004045724729064204, 'min_child_weight': 1, 'subsample': 0.9331559720774428, 'colsample_bytree': 0.5844164508168194, 'reg_alpha': 2.742025068307707e-05, 'reg_lambda': 0.009885387517462787}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,443] Trial 182 finished with value: 0.9688253775210296 and parameters: {'n_estimators': 571, 'max_depth': 2, 'learning_rate': 0.30577243814461674, 'gamma': 0.012880627685399902, 'min_child_weight': 1, 'subsample': 0.9485931009156126, 'colsample_bytree': 0.5996568259313692, 'reg_alpha': 1.3396606182173234e-05, 'reg_lambda': 0.007635969022558665}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,535] Trial 183 finished with value: 0.9674166413296849 and parameters: {'n_estimators': 629, 'max_depth': 3, 'learning_rate': 0.28188713644457714, 'gamma': 0.005235909540075137, 'min_child_weight': 1, 'subsample': 0.961053367499909, 'colsample_bytree': 0.6198251105511885, 'reg_alpha': 2.5215043925068256e-05, 'reg_lambda': 0.002628148822304905}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,589] Trial 184 finished with value: 0.9649437519002737 and parameters: {'n_estimators': 67, 'max_depth': 3, 'learning_rate': 0.35529559929163035, 'gamma': 0.001225158706094834, 'min_child_weight': 1, 'subsample': 0.9338994225805587, 'colsample_bytree': 0.5674075089505664, 'reg_alpha': 0.08714908351909771, 'reg_lambda': 0.004961439672981354}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,681] Trial 185 finished with value: 0.965017229147664 and parameters: {'n_estimators': 607, 'max_depth': 2, 'learning_rate': 0.3839038757913715, 'gamma': 0.002331336980927999, 'min_child_weight': 1, 'subsample': 0.9892104914873026, 'colsample_bytree': 0.5192707137105969, 'reg_alpha': 7.812769802730331e-05, 'reg_lambda': 0.033524561228580545}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,774] Trial 186 finished with value: 0.9667148069321984 and parameters: {'n_estimators': 835, 'max_depth': 6, 'learning_rate': 0.3428772238998707, 'gamma': 0.004906203351066525, 'min_child_weight': 1, 'subsample': 0.9769488668693691, 'colsample_bytree': 0.5510092209217737, 'reg_alpha': 0.00013871818028374805, 'reg_lambda': 0.01985471270961442}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,841] Trial 187 finished with value: 0.9673913043478259 and parameters: {'n_estimators': 253, 'max_depth': 4, 'learning_rate': 0.32508797810579004, 'gamma': 0.0009561938888235766, 'min_child_weight': 1, 'subsample': 0.9161395624008124, 'colsample_bytree': 0.9607189113456386, 'reg_alpha': 9.607969314415795e-06, 'reg_lambda': 1.3099693721755294e-05}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,920] Trial 188 finished with value: 0.9691547582851932 and parameters: {'n_estimators': 546, 'max_depth': 5, 'learning_rate': 0.295502717565899, 'gamma': 0.009464505555965745, 'min_child_weight': 1, 'subsample': 0.9248654467114628, 'colsample_bytree': 0.5093090629574039, 'reg_alpha': 3.311414049778045e-05, 'reg_lambda': 0.011358963682681302}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:55,999] Trial 189 finished with value: 0.9682755650146954 and parameters: {'n_estimators': 640, 'max_depth': 8, 'learning_rate': 0.3600401699105416, 'gamma': 8.633600075102984e-07, 'min_child_weight': 7, 'subsample': 0.9529371337244095, 'colsample_bytree': 0.5793876812256805, 'reg_alpha': 1.854830942484543e-05, 'reg_lambda': 0.0071807775805754264}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,077] Trial 190 finished with value: 0.9641785750481402 and parameters: {'n_estimators': 580, 'max_depth': 1, 'learning_rate': 0.3955258955416034, 'gamma': 0.0028855432380126994, 'min_child_weight': 1, 'subsample': 0.6558300232658375, 'colsample_bytree': 0.532053023783299, 'reg_alpha': 5.025989847819503e-05, 'reg_lambda': 0.0003699564761924533}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,170] Trial 191 finished with value: 0.9765556906861255 and parameters: {'n_estimators': 575, 'max_depth': 8, 'learning_rate': 0.36859695453147573, 'gamma': 0.00017562327914148257, 'min_child_weight': 1, 'subsample': 0.9949295139298673, 'colsample_bytree': 0.504238342895176, 'reg_alpha': 5.494592850652422e-06, 'reg_lambda': 0.05999590732038283}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,260] Trial 192 finished with value: 0.9762187088274045 and parameters: {'n_estimators': 597, 'max_depth': 8, 'learning_rate': 0.37669387399080473, 'gamma': 0.0001054246260196604, 'min_child_weight': 1, 'subsample': 0.9911385292858662, 'colsample_bytree': 0.5008474674992347, 'reg_alpha': 3.775728586579843e-06, 'reg_lambda': 0.06070795069378114}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,338] Trial 193 finished with value: 0.9697603121516163 and parameters: {'n_estimators': 565, 'max_depth': 8, 'learning_rate': 0.3733367211586875, 'gamma': 0.00010171868639087341, 'min_child_weight': 1, 'subsample': 0.9885402527271766, 'colsample_bytree': 0.503296796362895, 'reg_alpha': 3.156842485650543e-06, 'reg_lambda': 0.10114525177731656}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,432] Trial 194 finished with value: 0.9722965440356746 and parameters: {'n_estimators': 618, 'max_depth': 9, 'learning_rate': 0.36465218306972474, 'gamma': 0.000132198680326127, 'min_child_weight': 1, 'subsample': 0.9998270693902586, 'colsample_bytree': 0.5003410098501623, 'reg_alpha': 5.171884685209688e-06, 'reg_lambda': 0.048537409450488525}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,524] Trial 195 finished with value: 0.9762187088274045 and parameters: {'n_estimators': 699, 'max_depth': 8, 'learning_rate': 0.3840175223825088, 'gamma': 2.8688603044497538e-05, 'min_child_weight': 1, 'subsample': 0.9791585243331079, 'colsample_bytree': 0.5177740106795239, 'reg_alpha': 1.985570244508912e-06, 'reg_lambda': 0.0850937565995448}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,616] Trial 196 finished with value: 0.9731351981351981 and parameters: {'n_estimators': 704, 'max_depth': 8, 'learning_rate': 0.3845510622747572, 'gamma': 3.2293045599745385e-05, 'min_child_weight': 1, 'subsample': 0.9708751000446808, 'colsample_bytree': 0.5160888376342883, 'reg_alpha': 1.1285147244308468e-06, 'reg_lambda': 0.07777113981412653}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,707] Trial 197 finished with value: 0.9740194588020676 and parameters: {'n_estimators': 686, 'max_depth': 7, 'learning_rate': 0.3807493855934895, 'gamma': 4.962483143323837e-05, 'min_child_weight': 1, 'subsample': 0.9825848909958048, 'colsample_bytree': 0.5164570385938616, 'reg_alpha': 2.365763358102613e-06, 'reg_lambda': 0.13749590646470938}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,799] Trial 198 finished with value: 0.9669251038816256 and parameters: {'n_estimators': 679, 'max_depth': 7, 'learning_rate': 0.39587927481041185, 'gamma': 6.076559520990681e-06, 'min_child_weight': 2, 'subsample': 0.980027070691821, 'colsample_bytree': 0.5121661148934848, 'reg_alpha': 2.1636220457836166e-06, 'reg_lambda': 0.1981344625178931}. Best is trial 87 with value: 0.9775793047532177.\n", - "[I 2025-08-18 23:04:56,894] Trial 199 finished with value: 0.9730085132259045 and parameters: {'n_estimators': 734, 'max_depth': 8, 'learning_rate': 0.3827459493351444, 'gamma': 5.577111965000543e-05, 'min_child_weight': 1, 'subsample': 0.9874622359136933, 'colsample_bytree': 0.524715757741188, 'reg_alpha': 2.583619561021487e-06, 'reg_lambda': 0.12564000314896498}. Best is trial 87 with value: 0.9775793047532177.\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**LinearBoost results:**" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best trial:\n", - "F1 Score: 0.977579\n", - "Parameters:\n", - "n_estimators: 636\n", - "max_depth: 3\n", - "learning_rate: 0.28911459468011935\n", - "gamma: 0.0026877179567177173\n", - "min_child_weight: 1\n", - "subsample: 0.9884898945689472\n", - "colsample_bytree: 0.5529899112143574\n", - "reg_alpha: 8.780578569353003e-06\n", - "reg_lambda: 0.024175358439225716\n" - ] - } - ], - "source": [ - "import xgboost as xgb\n", - "\n", - "\n", - "def objective(trial):\n", - " params = {\n", - " \"objective\": \"binary:logistic\",\n", - " \"use_label_encoder\": False,\n", - " \"n_estimators\": trial.suggest_int(\"n_estimators\", 20, 1000),\n", - " \"max_depth\": trial.suggest_int(\"max_depth\", 1, 20),\n", - " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 0.7),\n", - " \"gamma\": trial.suggest_float(\"gamma\", 1e-8, 1.0, log=True),\n", - " \"min_child_weight\": trial.suggest_int(\"min_child_weight\", 1, 10),\n", - " \"subsample\": trial.suggest_float(\"subsample\", 0.5, 1.0),\n", - " \"colsample_bytree\": trial.suggest_float(\"colsample_bytree\", 0.5, 1.0),\n", - " \"reg_alpha\": trial.suggest_float(\"reg_alpha\", 1e-8, 1.0, log=True),\n", - " \"reg_lambda\": trial.suggest_float(\"reg_lambda\", 1e-8, 1.0, log=True),\n", - " \"enable_categorical\": True,\n", - " \"eval_metric\": \"logloss\",\n", - " }\n", - "\n", - " model = xgb.XGBClassifier(**params)\n", - "\n", - " scores = cross_val_score(\n", - " estimator=model,\n", - " X=X,\n", - " y=y,\n", - " scoring=\"f1_weighted\",\n", - " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", - " n_jobs=-1,\n", - " )\n", - "\n", - " return scores.mean()\n", - "\n", - "\n", - "study = optuna.create_study(direction=\"maximize\")\n", - "study.optimize(objective, n_trials=200)\n", - "\n", - "best_trial = study.best_trial\n", - "\n", - "print(\"Best trial:\")\n", - "print(f\"F1 Score: {best_trial.value:.6f}\")\n", - "print(\"Parameters:\")\n", - "for k, v in best_trial.params.items():\n", - " print(f\"{k}: {v}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**LightGBM results:**" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:02:02,037] A new study created in memory with name: no-name-82933463-2c1e-432a-893e-8dccaf42a971\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:02:02,719] Trial 0 finished with value: 0.6404040390084329 and parameters: {'n_estimators': 98, 'learning_rate': 0.025040969870000332, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.0036506834438673618, 'degree': 5, 'coef0': 0.3301750124911056}. Best is trial 0 with value: 0.6404040390084329.\n", + "[I 2025-08-19 22:02:03,124] Trial 1 finished with value: 0.5345075877473346 and parameters: {'n_estimators': 223, 'learning_rate': 0.7297126647372456, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.8114762985242304, 'degree': 3, 'coef0': 0.427337620015356}. Best is trial 0 with value: 0.6404040390084329.\n", + "[I 2025-08-19 22:02:03,558] Trial 2 finished with value: 0.8435145697001879 and parameters: {'n_estimators': 400, 'learning_rate': 0.11869138844012254, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.005788104394731735}. Best is trial 2 with value: 0.8435145697001879.\n", + "[I 2025-08-19 22:02:03,711] Trial 3 finished with value: 0.8764210138920593 and parameters: {'n_estimators': 31, 'learning_rate': 0.030091383187136795, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 3 with value: 0.8764210138920593.\n", + "[I 2025-08-19 22:02:04,570] Trial 4 finished with value: 0.8185946867313308 and parameters: {'n_estimators': 319, 'learning_rate': 0.024091883364845683, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'linear'}. Best is trial 3 with value: 0.8764210138920593.\n", + "[I 2025-08-19 22:02:04,750] Trial 5 finished with value: 0.9017212906585973 and parameters: {'n_estimators': 87, 'learning_rate': 0.48142547555682524, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.12840098702472594}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:05,166] Trial 6 finished with value: 0.8300528334061669 and parameters: {'n_estimators': 86, 'learning_rate': 0.2164714650817863, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'sigmoid', 'gamma': 0.15920891724378544, 'coef0': 0.7539946866285475}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:07,510] Trial 7 finished with value: 0.6535195434381997 and parameters: {'n_estimators': 470, 'learning_rate': 0.012901892094153418, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'poly', 'gamma': 3.940362684702575, 'degree': 2, 'coef0': 0.4967650580245552}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:07,913] Trial 8 finished with value: 0.7971266517319944 and parameters: {'n_estimators': 452, 'learning_rate': 0.43676541330692303, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.0967500612488954}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,322] Trial 9 finished with value: 0.5694014450011219 and parameters: {'n_estimators': 243, 'learning_rate': 0.012286177632393586, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 0.0026004536254413, 'degree': 4, 'coef0': 0.15054572715819692}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,587] Trial 10 finished with value: 0.8819567586691062 and parameters: {'n_estimators': 157, 'learning_rate': 0.2770406446126875, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.05370625210928932}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,829] Trial 11 finished with value: 0.8964421634266355 and parameters: {'n_estimators': 147, 'learning_rate': 0.3006331948489542, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.03955509407249669}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:09,971] Trial 12 finished with value: 0.8521240202153993 and parameters: {'n_estimators': 172, 'learning_rate': 0.9988817093993582, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.023490983805136197}. Best is trial 5 with value: 0.9017212906585973.\n", + "[I 2025-08-19 22:02:10,237] Trial 13 finished with value: 0.9263770712127013 and parameters: {'n_estimators': 35, 'learning_rate': 0.10250765731473209, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.6514127677245307}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:10,424] Trial 14 finished with value: 0.7085679744920659 and parameters: {'n_estimators': 21, 'learning_rate': 0.07966081404443828, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'sigmoid', 'gamma': 0.6310102946471119, 'coef0': 0.9639953544051878}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:10,506] Trial 15 finished with value: 0.5418932173176405 and parameters: {'n_estimators': 315, 'learning_rate': 0.08759215611783155, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 8.453910649175267}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:10,948] Trial 16 finished with value: 0.9031163163136877 and parameters: {'n_estimators': 76, 'learning_rate': 0.052469928102373574, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.5675836541180403}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:11,057] Trial 17 finished with value: 0.7550115293636145 and parameters: {'n_estimators': 13, 'learning_rate': 0.044871824661281395, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8086407703773626}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:11,526] Trial 18 finished with value: 0.53092297245577 and parameters: {'n_estimators': 78, 'learning_rate': 0.1330897164081811, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 2.267555816096478, 'coef0': 0.014870765902805116}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:12,002] Trial 19 finished with value: 0.8675858847685067 and parameters: {'n_estimators': 207, 'learning_rate': 0.05154796109273011, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:12,485] Trial 20 finished with value: 0.9088656344540121 and parameters: {'n_estimators': 303, 'learning_rate': 0.16750558381714575, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.29744031601691207}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:12,954] Trial 21 finished with value: 0.9206498285402447 and parameters: {'n_estimators': 299, 'learning_rate': 0.17348345914734523, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.5243817676865739}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:13,447] Trial 22 finished with value: 0.9115464653740457 and parameters: {'n_estimators': 309, 'learning_rate': 0.1966185423007268, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.27828466414571096}. Best is trial 13 with value: 0.9263770712127013.\n", + "[I 2025-08-19 22:02:14,378] Trial 23 finished with value: 0.9462108116357341 and parameters: {'n_estimators': 369, 'learning_rate': 0.16073435877818204, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9847789259555744}. Best is trial 23 with value: 0.9462108116357341.\n", + "[I 2025-08-19 22:02:15,192] Trial 24 finished with value: 0.9461696031015109 and parameters: {'n_estimators': 361, 'learning_rate': 0.07835520681588722, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.0987046014422583}. Best is trial 23 with value: 0.9462108116357341.\n", + "[I 2025-08-19 22:02:16,105] Trial 25 finished with value: 0.9517798886901965 and parameters: {'n_estimators': 375, 'learning_rate': 0.07269841814479387, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.209952371165283}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:16,984] Trial 26 finished with value: 0.9324487995962987 and parameters: {'n_estimators': 379, 'learning_rate': 0.07230657816758931, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4187279689074788}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:18,776] Trial 27 finished with value: -inf and parameters: {'n_estimators': 374, 'learning_rate': 0.038575969507376164, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 4.714383316597883, 'coef0': 0.7803535797752535}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:19,167] Trial 28 finished with value: 0.8709779688748764 and parameters: {'n_estimators': 421, 'learning_rate': 0.0746916847815778, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:21,551] Trial 29 finished with value: 0.7023921951486901 and parameters: {'n_estimators': 498, 'learning_rate': 0.02085363052154944, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 1.759102678934659, 'degree': 2, 'coef0': 0.6913894433614183}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:21,919] Trial 30 finished with value: 0.859909045397919 and parameters: {'n_estimators': 350, 'learning_rate': 0.060559050608611484, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.4952186713052695}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:23,126] Trial 31 finished with value: 0.9218746518721318 and parameters: {'n_estimators': 354, 'learning_rate': 0.1280653186238248, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8616818169187364}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:23,988] Trial 32 finished with value: 0.9296865784287618 and parameters: {'n_estimators': 410, 'learning_rate': 0.07021730970300748, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7746356369809244}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:24,184] Trial 33 finished with value: 0.8116240901405313 and parameters: {'n_estimators': 276, 'learning_rate': 0.10871708293585933, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 9.388110391883588}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:25,695] Trial 34 finished with value: 0.9293560948390669 and parameters: {'n_estimators': 383, 'learning_rate': 0.034156266307402705, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.429084842782736}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:25,856] Trial 35 finished with value: 0.5852644581410708 and parameters: {'n_estimators': 426, 'learning_rate': 0.1511859326143314, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 1.2486026815845557, 'degree': 5, 'coef0': 0.9704353144695104}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:26,306] Trial 36 finished with value: 0.8763231749616842 and parameters: {'n_estimators': 344, 'learning_rate': 0.09526097425921956, 'algorithm': 'SAMME.R', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:27,781] Trial 37 finished with value: 0.9018423220481535 and parameters: {'n_estimators': 380, 'learning_rate': 0.019876822774381235, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.724771837650152}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:28,517] Trial 38 finished with value: 0.9202747486761362 and parameters: {'n_estimators': 453, 'learning_rate': 0.06647223380069087, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.1084783848378548}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:28,942] Trial 39 finished with value: 0.8628370095777891 and parameters: {'n_estimators': 273, 'learning_rate': 0.269922262432126, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.0066123931064254555}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:30,565] Trial 40 finished with value: 0.8050021872275455 and parameters: {'n_estimators': 332, 'learning_rate': 0.02933776477103744, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 0.27010729641241976, 'coef0': 0.22133988641045943}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:31,335] Trial 41 finished with value: 0.9268901508585747 and parameters: {'n_estimators': 411, 'learning_rate': 0.061902309242806756, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.8646613129693383}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:32,431] Trial 42 finished with value: 0.9240947416940678 and parameters: {'n_estimators': 398, 'learning_rate': 0.042508608956588166, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.786058859203096}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:32,890] Trial 43 finished with value: 0.8712087231269168 and parameters: {'n_estimators': 441, 'learning_rate': 0.07930266596666663, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.848021414105109}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:33,835] Trial 44 finished with value: 0.8991133617676276 and parameters: {'n_estimators': 365, 'learning_rate': 0.12330246274809091, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.450448896004862}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:34,438] Trial 45 finished with value: 0.6983797615900317 and parameters: {'n_estimators': 482, 'learning_rate': 0.05239332207965422, 'algorithm': 'SAMME.R', 'scaler': 'quantile-normal', 'kernel': 'poly', 'gamma': 5.714276346847359, 'degree': 3, 'coef0': 0.6186051595258996}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:34,863] Trial 46 finished with value: 0.9293575787426139 and parameters: {'n_estimators': 394, 'learning_rate': 0.22829327401274127, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 0.9319488463371248}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:35,220] Trial 47 finished with value: 0.8181102705094435 and parameters: {'n_estimators': 439, 'learning_rate': 0.35502195035823503, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:36,664] Trial 48 finished with value: 0.846325632333387 and parameters: {'n_estimators': 469, 'learning_rate': 0.09448870280660304, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.0010087705216177958}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,219] Trial 49 finished with value: 0.9378935239732582 and parameters: {'n_estimators': 334, 'learning_rate': 0.07222234799412496, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.4323404856498683}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,371] Trial 50 finished with value: 0.932192378562819 and parameters: {'n_estimators': 334, 'learning_rate': 0.675761337925708, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3921347754260098}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,533] Trial 51 finished with value: 0.920993572883402 and parameters: {'n_estimators': 331, 'learning_rate': 0.8027321262951309, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.395150239747632}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:37,949] Trial 52 finished with value: 0.9459583919276465 and parameters: {'n_estimators': 283, 'learning_rate': 0.5044135952817085, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.9424173881795572}. Best is trial 25 with value: 0.9517798886901965.\n", + "[I 2025-08-19 22:02:38,333] Trial 53 finished with value: 0.9543374173629988 and parameters: {'n_estimators': 239, 'learning_rate': 0.5595716808885748, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.647241725838371}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:38,436] Trial 54 finished with value: 0.8514265280726686 and parameters: {'n_estimators': 227, 'learning_rate': 0.48409844695819165, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 4.125551830420961}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:38,683] Trial 55 finished with value: 0.8281731307797214 and parameters: {'n_estimators': 193, 'learning_rate': 0.5985975447789242, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.586444926695531}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:38,721] Trial 56 finished with value: -inf and parameters: {'n_estimators': 278, 'learning_rate': 0.3864373743263281, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 9.558029039004188, 'coef0': 0.02372150656881622}. Best is trial 53 with value: 0.9543374173629988.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Trial failed with exception: \n", + "All the 10 fits failed.\n", + "It is very likely that your model is misconfigured.\n", + "You can try to debug the error by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/pipeline.py\", line 662, in fit\n", + " self._final_estimator.fit(Xt, y, **last_step_params[\"fit\"])\n", + " ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 628, in fit\n", + " return super().fit(training_data, y, sample_weight)\n", + " ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/ensemble/_weight_boosting.py\", line 167, in fit\n", + " sample_weight, estimator_weight, estimator_error = self._boost(\n", + " ~~~~~~~~~~~^\n", + " iboost, X, y, sample_weight, random_state\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 702, in _boost\n", + " raise ValueError(\n", + " \"BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\"\n", + " )\n", + "ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:02:39,055] Trial 57 finished with value: 0.8717863235369474 and parameters: {'n_estimators': 257, 'learning_rate': 0.5013464948241906, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.4424401922925503}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:39,588] Trial 58 finished with value: 0.6882396202694265 and parameters: {'n_estimators': 293, 'learning_rate': 0.31142751907125016, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'poly', 'gamma': 3.613839721994584, 'degree': 4, 'coef0': 0.32280671741188566}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:39,778] Trial 59 finished with value: 0.8819539998922167 and parameters: {'n_estimators': 233, 'learning_rate': 0.6097668080397359, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.08883583450139441}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:40,441] Trial 60 finished with value: 0.9281749115310631 and parameters: {'n_estimators': 204, 'learning_rate': 0.1538995463327668, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.9153016198187663}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:40,637] Trial 61 finished with value: 0.9239378580080395 and parameters: {'n_estimators': 361, 'learning_rate': 0.8920930290523721, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.069795607208937}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:41,236] Trial 62 finished with value: 0.9377972940442809 and parameters: {'n_estimators': 319, 'learning_rate': 0.08221986476116154, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2190944381431885}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:41,517] Trial 63 finished with value: 0.862790627424238 and parameters: {'n_estimators': 317, 'learning_rate': 0.08593415530250405, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 6.749002498833249}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:42,108] Trial 64 finished with value: 0.9353188132686524 and parameters: {'n_estimators': 257, 'learning_rate': 0.0561150028803941, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7932014212856044}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:42,349] Trial 65 finished with value: 0.8649001790723136 and parameters: {'n_estimators': 297, 'learning_rate': 0.11050826854916225, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:43,076] Trial 66 finished with value: 0.9266398313868034 and parameters: {'n_estimators': 118, 'learning_rate': 0.04607008180795451, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8383575083908024}. Best is trial 53 with value: 0.9543374173629988.\n", + "[I 2025-08-19 22:02:44,106] Trial 67 finished with value: 0.9546503958241553 and parameters: {'n_estimators': 247, 'learning_rate': 0.21347325986729773, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1809425528201563}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:44,846] Trial 68 finished with value: 0.6989186486192198 and parameters: {'n_estimators': 236, 'learning_rate': 0.429627157442039, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 0.012260381856754793, 'coef0': 0.8372686886361344}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:45,094] Trial 69 finished with value: 0.9354147103952727 and parameters: {'n_estimators': 173, 'learning_rate': 0.18642494354170872, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.476492775061456}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:45,787] Trial 70 finished with value: 0.9293575787426139 and parameters: {'n_estimators': 282, 'learning_rate': 0.14066067971814394, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.6966820470759123}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:46,568] Trial 71 finished with value: 0.9544562382246768 and parameters: {'n_estimators': 265, 'learning_rate': 0.22209149104576692, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2304812552325375}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:47,354] Trial 72 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 254, 'learning_rate': 0.2565268037020722, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8661220775520375}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:48,126] Trial 73 finished with value: 0.9546241015332697 and parameters: {'n_estimators': 210, 'learning_rate': 0.2281741451600984, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.936522572088527}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:48,879] Trial 74 finished with value: 0.9517579938498862 and parameters: {'n_estimators': 210, 'learning_rate': 0.2191416530172179, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6401238802616942}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:49,874] Trial 75 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 214, 'learning_rate': 0.22967638326768033, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.635572239547895}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:50,292] Trial 76 finished with value: 0.9283794764556614 and parameters: {'n_estimators': 214, 'learning_rate': 0.23287522337623806, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 0.3983494805126542}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:51,082] Trial 77 finished with value: 0.6705043315571843 and parameters: {'n_estimators': 188, 'learning_rate': 0.25405001864614346, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 1.592417751058729, 'degree': 5, 'coef0': 0.6291303425648905}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:51,718] Trial 78 finished with value: 0.9489535935383199 and parameters: {'n_estimators': 148, 'learning_rate': 0.20184930543138635, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0930264745806801}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:52,130] Trial 79 finished with value: 0.8530369159459188 and parameters: {'n_estimators': 249, 'learning_rate': 0.3425617353986758, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.18880724810140742}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:52,324] Trial 80 finished with value: 0.8759702338461084 and parameters: {'n_estimators': 214, 'learning_rate': 0.28502977258205575, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:52,948] Trial 81 finished with value: 0.9432049461723968 and parameters: {'n_estimators': 154, 'learning_rate': 0.20123449299861937, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.1197804185074935}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:53,558] Trial 82 finished with value: 0.94320286269291 and parameters: {'n_estimators': 136, 'learning_rate': 0.244190328611221, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.424597717864778}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:54,092] Trial 83 finished with value: 0.9265953575750772 and parameters: {'n_estimators': 173, 'learning_rate': 0.2113131563444056, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.7751432908813656}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:54,385] Trial 84 finished with value: 0.9405676191829102 and parameters: {'n_estimators': 48, 'learning_rate': 0.1769465491916037, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.1317701234902864}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:55,155] Trial 85 finished with value: 0.9461117353464846 and parameters: {'n_estimators': 262, 'learning_rate': 0.3176795630787612, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 1.9190549701508972}. Best is trial 67 with value: 0.9546503958241553.\n", + "[I 2025-08-19 22:02:55,764] Trial 86 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 193, 'learning_rate': 0.26419239924556914, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.768323929854739}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:55,888] Trial 87 finished with value: 0.8515658309121397 and parameters: {'n_estimators': 182, 'learning_rate': 0.2722479790329728, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 8.067883543139013}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:56,452] Trial 88 finished with value: 0.5249054202956112 and parameters: {'n_estimators': 201, 'learning_rate': 0.3660228120243797, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 2.5435597533944367, 'coef0': 0.1625403380559477}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:56,745] Trial 89 finished with value: 0.9353761797823182 and parameters: {'n_estimators': 217, 'learning_rate': 0.14050947729651117, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.082668135626794}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:57,414] Trial 90 finished with value: 0.9461914397690464 and parameters: {'n_estimators': 243, 'learning_rate': 0.40636575903125277, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1374915009572724}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:58,083] Trial 91 finished with value: 0.9433191177151397 and parameters: {'n_estimators': 137, 'learning_rate': 0.2050658999304865, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6514217851524977}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:58,822] Trial 92 finished with value: 0.9432909030357621 and parameters: {'n_estimators': 225, 'learning_rate': 0.2222123184480564, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.331241527111629}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:02:59,426] Trial 93 finished with value: 0.9488798569635867 and parameters: {'n_estimators': 164, 'learning_rate': 0.17279265207727196, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.9933659596849163}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:00,176] Trial 94 finished with value: 0.9461776790778822 and parameters: {'n_estimators': 268, 'learning_rate': 0.31518497467892653, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.201533416805354}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:00,537] Trial 95 finished with value: 0.9350713788373026 and parameters: {'n_estimators': 110, 'learning_rate': 0.2548250311872609, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.602537975876707}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:01,442] Trial 96 finished with value: 0.9428383837566567 and parameters: {'n_estimators': 197, 'learning_rate': 0.16383718909942865, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.74429116577557}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:02,495] Trial 97 finished with value: 0.6941801663418611 and parameters: {'n_estimators': 236, 'learning_rate': 0.19045988916497364, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 0.5507502417499932, 'degree': 3, 'coef0': 0.5212178203250792}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:02,893] Trial 98 finished with value: 0.9372552798787337 and parameters: {'n_estimators': 183, 'learning_rate': 0.2738956005721183, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 1.5112047541146179}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:03,158] Trial 99 finished with value: 0.8305296592545964 and parameters: {'n_estimators': 243, 'learning_rate': 0.22214604361651502, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 0.034548703205194466}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:03,330] Trial 100 finished with value: 0.8578592756814178 and parameters: {'n_estimators': 211, 'learning_rate': 0.33169917655289977, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:03,885] Trial 101 finished with value: 0.9377234617768158 and parameters: {'n_estimators': 157, 'learning_rate': 0.17626469712395465, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8986221438856852}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:04,576] Trial 102 finished with value: 0.9489822458261082 and parameters: {'n_estimators': 172, 'learning_rate': 0.293264685705061, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0710442197687955}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:05,435] Trial 103 finished with value: 0.8062559026857938 and parameters: {'n_estimators': 144, 'learning_rate': 0.010553067733616528, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.108454484699699}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:06,248] Trial 104 finished with value: 0.9432935743437543 and parameters: {'n_estimators': 226, 'learning_rate': 0.2975390616899621, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.1467167237895284}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:07,093] Trial 105 finished with value: 0.9518286923687628 and parameters: {'n_estimators': 192, 'learning_rate': 0.24331029503500007, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7495618454027402}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:08,068] Trial 106 finished with value: 0.9517352420116627 and parameters: {'n_estimators': 204, 'learning_rate': 0.26097714815919504, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7638013611577343}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:08,885] Trial 107 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 205, 'learning_rate': 0.252142149886663, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6815108553353053}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:09,304] Trial 108 finished with value: 0.899160357207285 and parameters: {'n_estimators': 251, 'learning_rate': 0.5668562989797123, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.9079402572030912}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:09,341] Trial 109 finished with value: -inf and parameters: {'n_estimators': 193, 'learning_rate': 0.37388674256800275, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 6.342042428769567, 'coef0': 0.8508850801893877}. Best is trial 86 with value: 0.9573878203541313.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Trial failed with exception: \n", + "All the 10 fits failed.\n", + "It is very likely that your model is misconfigured.\n", + "You can try to debug the error by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/pipeline.py\", line 662, in fit\n", + " self._final_estimator.fit(Xt, y, **last_step_params[\"fit\"])\n", + " ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 628, in fit\n", + " return super().fit(training_data, y, sample_weight)\n", + " ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/base.py\", line 1389, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/ensemble/_weight_boosting.py\", line 167, in fit\n", + " sample_weight, estimator_weight, estimator_error = self._boost(\n", + " ~~~~~~~~~~~^\n", + " iboost, X, y, sample_weight, random_state\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/src/linearboost/linear_boost.py\", line 702, in _boost\n", + " raise ValueError(\n", + " \"BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\"\n", + " )\n", + "ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit.\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-19 22:03:09,683] Trial 110 finished with value: 0.9354204269132287 and parameters: {'n_estimators': 223, 'learning_rate': 0.11525970851531234, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.42390474054593}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:10,337] Trial 111 finished with value: 0.9432228758248777 and parameters: {'n_estimators': 184, 'learning_rate': 0.2319177796947066, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3285933571091035}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:10,826] Trial 112 finished with value: 0.9547394467306798 and parameters: {'n_estimators': 172, 'learning_rate': 0.45079109156398994, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.2893364126109446}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:11,421] Trial 113 finished with value: 0.9377302419765551 and parameters: {'n_estimators': 235, 'learning_rate': 0.44759844230443413, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7122505150670086}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:11,715] Trial 114 finished with value: 0.9321772059231634 and parameters: {'n_estimators': 202, 'learning_rate': 0.6764856671426681, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9871144590689882}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:12,580] Trial 115 finished with value: 0.9460809161475096 and parameters: {'n_estimators': 222, 'learning_rate': 0.26207999753938394, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1480447330624464}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:13,366] Trial 116 finished with value: 0.9488718056362714 and parameters: {'n_estimators': 163, 'learning_rate': 0.14775843924623255, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.388882471501774}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:13,630] Trial 117 finished with value: 0.9322849692738714 and parameters: {'n_estimators': 268, 'learning_rate': 0.5585942165767696, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.6804771721860126}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:13,919] Trial 118 finished with value: 0.6905746692841864 and parameters: {'n_estimators': 243, 'learning_rate': 0.41799875124416175, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 3.3226800570154715, 'degree': 4, 'coef0': 0.3764539706641709}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:14,007] Trial 119 finished with value: 0.5473898159570962 and parameters: {'n_estimators': 213, 'learning_rate': 0.23662858855680907, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 8.081957798626714}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:14,460] Trial 120 finished with value: 0.9404654768430832 and parameters: {'n_estimators': 178, 'learning_rate': 0.19303072025137125, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.7206005729161484}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:15,334] Trial 121 finished with value: 0.9433827529207601 and parameters: {'n_estimators': 195, 'learning_rate': 0.27516173815741723, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.092849002219574}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:15,773] Trial 122 finished with value: 0.9433011880626585 and parameters: {'n_estimators': 169, 'learning_rate': 0.28751301328977386, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.2666489829518957}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:16,350] Trial 123 finished with value: 0.9489562648463121 and parameters: {'n_estimators': 206, 'learning_rate': 0.34002413096362905, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.791063939373234}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:17,309] Trial 124 finished with value: 0.948832689197155 and parameters: {'n_estimators': 231, 'learning_rate': 0.21115067056784395, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.552707016459578}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:17,630] Trial 125 finished with value: 0.8853569770206734 and parameters: {'n_estimators': 288, 'learning_rate': 0.2994230095220126, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.5219698007306968}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:17,858] Trial 126 finished with value: 0.9461482472660036 and parameters: {'n_estimators': 187, 'learning_rate': 0.7884721750296556, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.170239804867078}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:18,074] Trial 127 finished with value: 0.8714309902246997 and parameters: {'n_estimators': 126, 'learning_rate': 0.24054334690540302, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:18,548] Trial 128 finished with value: 0.9012734581578833 and parameters: {'n_estimators': 256, 'learning_rate': 0.38409733682042313, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.4191660723818265}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:18,872] Trial 129 finished with value: 0.9349763660408265 and parameters: {'n_estimators': 193, 'learning_rate': 0.47044486253274354, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.0705422821711204}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:19,413] Trial 130 finished with value: 0.9434181820431042 and parameters: {'n_estimators': 176, 'learning_rate': 0.21850684780654933, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.5125467723090513}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:20,153] Trial 131 finished with value: 0.9460737251637724 and parameters: {'n_estimators': 206, 'learning_rate': 0.2531366441565206, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.7267950905931142}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:20,897] Trial 132 finished with value: 0.9490707723468574 and parameters: {'n_estimators': 165, 'learning_rate': 0.18760740530924705, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.265656983620488}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:21,743] Trial 133 finished with value: 0.943311571394499 and parameters: {'n_estimators': 164, 'learning_rate': 0.19086079419695584, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.2097265572609297}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:22,476] Trial 134 finished with value: 0.9516409872982872 and parameters: {'n_estimators': 217, 'learning_rate': 0.29735193665249443, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.770599254653628}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:23,321] Trial 135 finished with value: 0.9517444082110016 and parameters: {'n_estimators': 218, 'learning_rate': 0.1632302131953216, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.040113453036413}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:24,014] Trial 136 finished with value: 0.9516815633204476 and parameters: {'n_estimators': 218, 'learning_rate': 0.16882720694545292, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.942970319501494}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:25,170] Trial 137 finished with value: -inf and parameters: {'n_estimators': 247, 'learning_rate': 0.1278287180708752, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 4.846425871954481, 'coef0': 0.25306830107690254}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:25,930] Trial 138 finished with value: 0.946129038490311 and parameters: {'n_estimators': 237, 'learning_rate': 0.10010032101446002, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.968090929872483}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:26,354] Trial 139 finished with value: 0.9463381854964412 and parameters: {'n_estimators': 231, 'learning_rate': 0.15840971565975542, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7352933426106074}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:27,210] Trial 140 finished with value: 0.9460938056940037 and parameters: {'n_estimators': 211, 'learning_rate': 0.17239197988266658, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.3235504334453292}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:27,967] Trial 141 finished with value: 0.9487049848424336 and parameters: {'n_estimators': 219, 'learning_rate': 0.21300438495163315, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.790899376657866}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:28,731] Trial 142 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 219, 'learning_rate': 0.23442872811180468, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.6011804785275734}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:29,792] Trial 143 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 264, 'learning_rate': 0.20570915176817917, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.8695111203697865}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:30,746] Trial 144 finished with value: 0.9374704190223566 and parameters: {'n_estimators': 195, 'learning_rate': 0.22711948376345956, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.417921813995831}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:31,517] Trial 145 finished with value: 0.9490205693199103 and parameters: {'n_estimators': 220, 'learning_rate': 0.1523444667474847, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.36120407727575}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:32,074] Trial 146 finished with value: 0.946030122496716 and parameters: {'n_estimators': 307, 'learning_rate': 0.24890881861731973, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.228147164535369}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:33,353] Trial 147 finished with value: 0.7023921951486901 and parameters: {'n_estimators': 251, 'learning_rate': 0.18049116357783734, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 2.1660641663421627, 'degree': 2, 'coef0': 0.5060218846433415}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:33,449] Trial 148 finished with value: 0.8791645618408939 and parameters: {'n_estimators': 227, 'learning_rate': 0.13354408856364375, 'algorithm': 'SAMME.R', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 5.979046347062491}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:33,784] Trial 149 finished with value: 0.9054841227029135 and parameters: {'n_estimators': 199, 'learning_rate': 0.16667582378735823, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 1.4840202886913443}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:34,114] Trial 150 finished with value: 0.9166507172958607 and parameters: {'n_estimators': 186, 'learning_rate': 0.26720591763623947, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.07839370990501919}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:34,758] Trial 151 finished with value: 0.9138729963208455 and parameters: {'n_estimators': 216, 'learning_rate': 0.2302042750507537, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1122679138806006}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:35,507] Trial 152 finished with value: 0.9573878203541313 and parameters: {'n_estimators': 241, 'learning_rate': 0.31520505133488197, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.6944891555683936}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:36,306] Trial 153 finished with value: 0.9461636352536825 and parameters: {'n_estimators': 239, 'learning_rate': 0.3236701702197362, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9127662798338538}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:37,049] Trial 154 finished with value: 0.9462952708457747 and parameters: {'n_estimators': 207, 'learning_rate': 0.3535507455857343, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.58334971605361}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:37,463] Trial 155 finished with value: 0.9461336301867951 and parameters: {'n_estimators': 272, 'learning_rate': 0.5199391044125163, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.676357734051705}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:37,874] Trial 156 finished with value: 0.8602959645297137 and parameters: {'n_estimators': 258, 'learning_rate': 0.27012467250976774, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.0019893842962743474}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:38,092] Trial 157 finished with value: 0.8703560070298408 and parameters: {'n_estimators': 229, 'learning_rate': 0.20094439327024868, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:38,652] Trial 158 finished with value: 0.9435799175554489 and parameters: {'n_estimators': 248, 'learning_rate': 0.24458403490438416, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.4585405054559875}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:39,478] Trial 159 finished with value: 0.9519111763632015 and parameters: {'n_estimators': 206, 'learning_rate': 0.06428014850687971, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.5236712354238175}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:40,291] Trial 160 finished with value: 0.9462496595153113 and parameters: {'n_estimators': 182, 'learning_rate': 0.06148345147359303, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.511917074131766}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:41,296] Trial 161 finished with value: 0.9433997373083892 and parameters: {'n_estimators': 200, 'learning_rate': 0.056282449823456975, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9714411114029415}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:42,007] Trial 162 finished with value: 0.935001884879774 and parameters: {'n_estimators': 210, 'learning_rate': 0.06614387596029363, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.7849457122146224}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:42,583] Trial 163 finished with value: 0.9460030266448959 and parameters: {'n_estimators': 223, 'learning_rate': 0.22164397237087538, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.232096588027822}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:43,298] Trial 164 finished with value: 0.9518914317907727 and parameters: {'n_estimators': 242, 'learning_rate': 0.08837430701870018, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.371958876189318}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:44,152] Trial 165 finished with value: 0.9461927188922579 and parameters: {'n_estimators': 238, 'learning_rate': 0.07360033276030915, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.639784254485829}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:45,001] Trial 166 finished with value: 0.9489818082176974 and parameters: {'n_estimators': 254, 'learning_rate': 0.07908133007358858, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.219443385176234}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:45,325] Trial 167 finished with value: 0.9211705188978586 and parameters: {'n_estimators': 189, 'learning_rate': 0.6303367464202104, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.3593735751901277}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:46,049] Trial 168 finished with value: 0.5371120525831441 and parameters: {'n_estimators': 242, 'learning_rate': 0.3106508834294839, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'sigmoid', 'gamma': 1.809149011162188, 'coef0': 0.9029906019159136}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:46,522] Trial 169 finished with value: 0.9351877596174386 and parameters: {'n_estimators': 231, 'learning_rate': 0.10364929586198274, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.572489372413239}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:47,500] Trial 170 finished with value: 0.9432840356506091 and parameters: {'n_estimators': 205, 'learning_rate': 0.08771082293345642, 'algorithm': 'SAMME.R', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.4686214773634303}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:48,332] Trial 171 finished with value: 0.9462224888474111 and parameters: {'n_estimators': 218, 'learning_rate': 0.23476923003084876, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.830028745713152}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:49,452] Trial 172 finished with value: 0.8773099501946401 and parameters: {'n_estimators': 225, 'learning_rate': 0.06587675146124812, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.016926388284853246}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:49,750] Trial 173 finished with value: 0.9265768775169478 and parameters: {'n_estimators': 197, 'learning_rate': 0.2652275469166709, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.8718946130665782}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:50,409] Trial 174 finished with value: 0.9544099308018232 and parameters: {'n_estimators': 280, 'learning_rate': 0.19683229184220954, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.2028559208805314}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:51,383] Trial 175 finished with value: 0.9490737209676066 and parameters: {'n_estimators': 281, 'learning_rate': 0.09276801286379756, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.0247920489149362}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:51,733] Trial 176 finished with value: 0.9297117181894698 and parameters: {'n_estimators': 263, 'learning_rate': 0.19306420905714758, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 5.146986179162074}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:52,924] Trial 177 finished with value: 0.9488718056362714 and parameters: {'n_estimators': 272, 'learning_rate': 0.21075557604381384, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4622172042445536}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:53,812] Trial 178 finished with value: 0.6905746692841864 and parameters: {'n_estimators': 242, 'learning_rate': 0.2472431025104272, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'poly', 'gamma': 3.4858813896883194, 'degree': 4, 'coef0': 0.09340899873225705}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:54,022] Trial 179 finished with value: 0.9347568931622089 and parameters: {'n_estimators': 254, 'learning_rate': 0.21538600767079638, 'algorithm': 'SAMME', 'scaler': 'quantile-uniform', 'kernel': 'rbf', 'gamma': 1.7390434014906178}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:55,197] Trial 180 finished with value: 0.9405344311859402 and parameters: {'n_estimators': 294, 'learning_rate': 0.0476544362356825, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.2260991184797905}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:55,869] Trial 181 finished with value: 0.9490340875605312 and parameters: {'n_estimators': 231, 'learning_rate': 0.181870970871893, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.992069313948637}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:56,653] Trial 182 finished with value: 0.9489625846853793 and parameters: {'n_estimators': 213, 'learning_rate': 0.27280377214301693, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.387474281739788}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:57,258] Trial 183 finished with value: 0.943466304385906 and parameters: {'n_estimators': 205, 'learning_rate': 0.2020747222080973, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 4.149925894026264}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:57,925] Trial 184 finished with value: 0.9461317097983033 and parameters: {'n_estimators': 191, 'learning_rate': 0.1618939225574238, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.8537724728291467}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:03:58,667] Trial 185 finished with value: 0.9546584631849069 and parameters: {'n_estimators': 388, 'learning_rate': 0.23172077548387995, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.305222179127677}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:00,019] Trial 186 finished with value: 0.9236047324399677 and parameters: {'n_estimators': 246, 'learning_rate': 0.015120439714314308, 'algorithm': 'SAMME', 'scaler': 'quantile-normal', 'kernel': 'rbf', 'gamma': 2.1574976046467467}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:00,646] Trial 187 finished with value: 0.943202024996045 and parameters: {'n_estimators': 395, 'learning_rate': 0.2901873392685005, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.6327993424719893}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:02,156] Trial 188 finished with value: 0.9488691343282791 and parameters: {'n_estimators': 413, 'learning_rate': 0.23690288538405274, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.9085381101542886}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:02,341] Trial 189 finished with value: 0.8768186259315769 and parameters: {'n_estimators': 347, 'learning_rate': 0.2249297866113301, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'linear'}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:03,570] Trial 190 finished with value: 0.9463066895734725 and parameters: {'n_estimators': 363, 'learning_rate': 0.24692399743713445, 'algorithm': 'SAMME', 'scaler': 'robust', 'kernel': 'rbf', 'gamma': 4.70397135863975}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:04,467] Trial 191 finished with value: 0.9517125575717025 and parameters: {'n_estimators': 405, 'learning_rate': 0.18927762197960674, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.0371730069380747}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:05,529] Trial 192 finished with value: 0.957290655564415 and parameters: {'n_estimators': 391, 'learning_rate': 0.186134731096261, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.1592388038658434}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:05,912] Trial 193 finished with value: 0.9195083329662423 and parameters: {'n_estimators': 377, 'learning_rate': 0.26404661468696655, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 0.14635960598805775}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:06,997] Trial 194 finished with value: 0.951698100788148 and parameters: {'n_estimators': 389, 'learning_rate': 0.21110976555505545, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 2.4076903818873254}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:07,849] Trial 195 finished with value: 0.9462224888474111 and parameters: {'n_estimators': 383, 'learning_rate': 0.29013599820311725, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.7990081861455174}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:08,719] Trial 196 finished with value: 0.951896719579647 and parameters: {'n_estimators': 397, 'learning_rate': 0.07357902059935685, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.5500892801338229}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:09,593] Trial 197 finished with value: 0.954692128744154 and parameters: {'n_estimators': 397, 'learning_rate': 0.0743400250121961, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.439866900092313}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:10,153] Trial 198 finished with value: 0.9407596316566416 and parameters: {'n_estimators': 418, 'learning_rate': 0.07062926587315435, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 3.3067035030172236}. Best is trial 86 with value: 0.9573878203541313.\n", + "[I 2025-08-19 22:04:10,880] Trial 199 finished with value: 0.9519222629510324 and parameters: {'n_estimators': 405, 'learning_rate': 0.07803729201336104, 'algorithm': 'SAMME', 'scaler': 'minmax', 'kernel': 'rbf', 'gamma': 1.4508904105515619}. Best is trial 86 with value: 0.9573878203541313.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Best trial:\n", + " Value (F1 Score): 0.9574\n", + " Parameters: \n", + " n_estimators: 193\n", + " learning_rate: 0.26419239924556914\n", + " algorithm: SAMME\n", + " scaler: minmax\n", + " kernel: rbf\n", + " gamma: 2.768323929854739\n" + ] + } + ], + "source": [ + "import optuna\n", + "import numpy as np\n", + "\n", + "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", + "from sklearn.preprocessing import OneHotEncoder\n", + "from sklearn.compose import ColumnTransformer, make_column_selector\n", + "from sklearn.pipeline import Pipeline\n", + "\n", + "# X, y assumed pre-defined (raw, with object/category cols intact)\n", + "\n", + "\n", + "def custom_loss(y_true, y_pred, weights):\n", + " return np.mean(weights * (y_true - y_pred) ** 2)\n", + "\n", + "\n", + "def _make_preprocessor() -> ColumnTransformer:\n", + " \"\"\"\n", + " Creates a preprocessor that only one-hot encodes categorical features\n", + " and passes numerical features through without scaling.\n", + " \"\"\"\n", + " return ColumnTransformer(\n", + " transformers=[\n", + " # The \"cat\" transformer applies OneHotEncoder to columns of type object or category.\n", + " (\n", + " \"cat\",\n", + " OneHotEncoder(handle_unknown=\"ignore\"),\n", + " make_column_selector(dtype_include=[\"object\", \"category\"]),\n", + " ),\n", + " ],\n", + " # 'remainder=\"passthrough\"' ensures that all other columns (i.e., numerical ones) are kept.\n", + " remainder=\"passthrough\",\n", + " n_jobs=None,\n", + " )\n", + "\n", + "\n", + "def objective(trial):\n", + " \"\"\"\n", + " Optuna objective function for hyperparameter tuning.\n", + " \"\"\"\n", + " # Define the search space for the classifier's parameters.\n", + " # The \"scaler\" parameter has been removed.\n", + " params = {\n", + " \"n_estimators\": trial.suggest_int(\"n_estimators\", 10, 500),\n", + " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 1.0, log=True),\n", + " \"algorithm\": trial.suggest_categorical(\"algorithm\", [\"SAMME\", \"SAMME.R\"]),\n", + " \"scaler\": trial.suggest_categorical(\n", + " \"scaler\", [\"minmax\", \"robust\", \"quantile-uniform\", \"quantile-normal\"]\n", + " ),\n", + " \"kernel\": trial.suggest_categorical(\n", + " \"kernel\", [\"linear\", \"rbf\", \"poly\", \"sigmoid\"]\n", + " ),\n", + " }\n", + " # Conditionally add parameters based on the chosen kernel.\n", + " if params[\"kernel\"] != \"linear\":\n", + " params[\"gamma\"] = trial.suggest_float(\"gamma\", 1e-3, 10.0, log=True)\n", + " if params[\"kernel\"] == \"poly\":\n", + " params[\"degree\"] = trial.suggest_int(\"degree\", 2, 5)\n", + " if params[\"kernel\"] in [\"poly\", \"sigmoid\"]:\n", + " params[\"coef0\"] = trial.suggest_float(\"coef0\", 0.0, 1.0)\n", + "\n", + " # Build a leakage-free pipeline for the trial.\n", + " # The preprocessor no longer requires a scaler argument.\n", + " pre = _make_preprocessor()\n", + "\n", + " # All items in `params` are now intended for the classifier.\n", + " clf = LinearBoostClassifier(**params)\n", + "\n", + " pipe = Pipeline(steps=[(\"preprocess\", pre), (\"model\", clf)])\n", + "\n", + " try:\n", + " # Perform stratified 10-fold cross-validation.\n", + " cv = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n", + " scores = cross_val_score(pipe, X, y, scoring=\"f1_weighted\", cv=cv)\n", + " # Return the mean F1 score, or negative infinity if scores contain NaN.\n", + " return -np.inf if np.isnan(scores).any() else scores.mean()\n", + " except Exception as e:\n", + " # Prune trial if an exception occurs (e.g., invalid parameter combination).\n", + " print(f\"Trial failed with exception: {e}\")\n", + " return -np.inf\n", + "\n", + "\n", + "# --- Optuna Study Execution ---\n", + "# Create a study object and specify the direction as \"maximize\" for F1 score.\n", + "study = optuna.create_study(direction=\"maximize\")\n", + "study.optimize(objective, n_trials=200)\n", + "\n", + "# --- Print Best Results ---\n", + "print(\"\\nBest trial:\")\n", + "best_trial = study.best_trial\n", + "print(f\" Value (F1 Score): {best_trial.value:.4f}\")\n", + "print(\" Parameters: \")\n", + "for key, value in best_trial.params.items():\n", + " print(f\" {key}: {value}\")" + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-18 21:38:31,112] A new study created in memory with name: no-name-a2c71fbc-43fe-4d55-a82d-10f7362f12f0\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", - "[W 2025-08-18 21:38:31,823] Trial 0 failed with parameters: {'boosting_type': 'gbdt', 'num_leaves': 231, 'learning_rate': 0.004729326807185178, 'n_estimators': 180, 'max_depth': 15, 'min_child_samples': 62, 'subsample': 0.95535818357979, 'colsample_bytree': 0.7438374709143218, 'reg_alpha': 1.0331517436951706e-05, 'reg_lambda': 1.2172287308521004e-05, 'min_split_gain': 4.144384519107149e-06, 'cat_smooth': 47, 'cat_l2': 2.5374071883620803e-07} because of the following error: ValueError('\\nAll the 10 fits failed.\\nIt is very likely that your model is misconfigured.\\nYou can try to debug the error by setting error_score=\\'raise\\'.\\n\\nBelow are more details about the failures:\\n--------------------------------------------------------------------------------\\n10 fits failed with the following error:\\nTraceback (most recent call last):\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\\n estimator.fit(X_train, y_train, **fit_params)\\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\\n super().fit(\\n ~~~~~~~~~~~^\\n X,\\n ^^\\n ...<12 lines>...\\n init_model=init_model,\\n ^^^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\\n self._Booster = train(\\n ~~~~~^\\n params=params,\\n ^^^^^^^^^^^^^^\\n ...<6 lines>...\\n callbacks=callbacks,\\n ^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\\n booster = Booster(params=params, train_set=train_set)\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\\n train_set.construct()\\n ~~~~~~~~~~~~~~~~~~~^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\\n self._lazy_init(\\n ~~~~~~~~~~~~~~~^\\n data=self.data,\\n ^^^^^^^^^^^^^^^\\n ...<9 lines>...\\n position=self.position,\\n ^^^^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\\n return self.set_feature_name(feature_name)\\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\\n _safe_call(\\n ~~~~~~~~~~^\\n _LIB.LGBM_DatasetSetFeatureNames(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n ...<3 lines>...\\n )\\n ^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\\n').\n", - "Traceback (most recent call last):\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py\", line 201, in _run_trial\n", - " value_or_values = func(trial)\n", - " File \"/var/folders/dj/6m_rn6_56pvb0zb7k0t6bz4r0000gn/T/ipykernel_47070/4223881388.py\", line 28, in objective\n", - " scores = cross_val_score(\n", - " estimator=model,\n", - " ...<4 lines>...\n", - " n_jobs=-1,\n", - " )\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py\", line 216, in wrapper\n", - " return func(*args, **kwargs)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 684, in cross_val_score\n", - " cv_results = cross_validate(\n", - " estimator=estimator,\n", - " ...<9 lines>...\n", - " error_score=error_score,\n", - " )\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py\", line 216, in wrapper\n", - " return func(*args, **kwargs)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 431, in cross_validate\n", - " _warn_or_raise_about_fit_failures(results, error_score)\n", - " ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 517, in _warn_or_raise_about_fit_failures\n", - " raise ValueError(all_fits_failed_message)\n", - "ValueError: \n", - "All the 10 fits failed.\n", - "It is very likely that your model is misconfigured.\n", - "You can try to debug the error by setting error_score='raise'.\n", - "\n", - "Below are more details about the failures:\n", - "--------------------------------------------------------------------------------\n", - "10 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n", - " super().fit(\n", - " ~~~~~~~~~~~^\n", - " X,\n", - " ^^\n", - " ...<12 lines>...\n", - " init_model=init_model,\n", - " ^^^^^^^^^^^^^^^^^^^^^^\n", - " )\n", - " ^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n", - " self._Booster = train(\n", - " ~~~~~^\n", - " params=params,\n", - " ^^^^^^^^^^^^^^\n", - " ...<6 lines>...\n", - " callbacks=callbacks,\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " )\n", - " ^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n", - " booster = Booster(params=params, train_set=train_set)\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n", - " train_set.construct()\n", - " ~~~~~~~~~~~~~~~~~~~^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n", - " self._lazy_init(\n", - " ~~~~~~~~~~~~~~~^\n", - " data=self.data,\n", - " ^^^^^^^^^^^^^^^\n", - " ...<9 lines>...\n", - " position=self.position,\n", - " ^^^^^^^^^^^^^^^^^^^^^^^\n", - " )\n", - " ^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n", - " return self.set_feature_name(feature_name)\n", - " ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n", - " _safe_call(\n", - " ~~~~~~~~~~^\n", - " _LIB.LGBM_DatasetSetFeatureNames(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " ...<3 lines>...\n", - " )\n", - " ^\n", - " )\n", - " ^\n", - " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n", - " raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\n", - "lightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n", - "\n", - "[W 2025-08-18 21:38:31,824] Trial 0 failed with value None.\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**XGBoost results:**" + ] }, { - "ename": "ValueError", - "evalue": "\nAll the 10 fits failed.\nIt is very likely that your model is misconfigured.\nYou can try to debug the error by setting error_score='raise'.\n\nBelow are more details about the failures:\n--------------------------------------------------------------------------------\n10 fits failed with the following error:\nTraceback (most recent call last):\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n estimator.fit(X_train, y_train, **fit_params)\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n super().fit(\n ~~~~~~~~~~~^\n X,\n ^^\n ...<12 lines>...\n init_model=init_model,\n ^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n self._Booster = train(\n ~~~~~^\n params=params,\n ^^^^^^^^^^^^^^\n ...<6 lines>...\n callbacks=callbacks,\n ^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n booster = Booster(params=params, train_set=train_set)\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n train_set.construct()\n ~~~~~~~~~~~~~~~~~~~^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n self._lazy_init(\n ~~~~~~~~~~~~~~~^\n data=self.data,\n ^^^^^^^^^^^^^^^\n ...<9 lines>...\n position=self.position,\n ^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n return self.set_feature_name(feature_name)\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n _safe_call(\n ~~~~~~~~~~^\n _LIB.LGBM_DatasetSetFeatureNames(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<3 lines>...\n )\n ^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mValueError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 41\u001b[39m\n\u001b[32m 37\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores.mean()\n\u001b[32m 40\u001b[39m study = optuna.create_study(direction=\u001b[33m\"\u001b[39m\u001b[33mmaximize\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m41\u001b[39m \u001b[43mstudy\u001b[49m\u001b[43m.\u001b[49m\u001b[43moptimize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobjective\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m200\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m best_trial = study.best_trial\n\u001b[32m 45\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mBest trial:\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/study.py:489\u001b[39m, in \u001b[36mStudy.optimize\u001b[39m\u001b[34m(self, func, n_trials, timeout, n_jobs, catch, callbacks, gc_after_trial, show_progress_bar)\u001b[39m\n\u001b[32m 387\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34moptimize\u001b[39m(\n\u001b[32m 388\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m 389\u001b[39m func: ObjectiveFuncType,\n\u001b[32m (...)\u001b[39m\u001b[32m 396\u001b[39m show_progress_bar: \u001b[38;5;28mbool\u001b[39m = \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[32m 397\u001b[39m ) -> \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m 398\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Optimize an objective function.\u001b[39;00m\n\u001b[32m 399\u001b[39m \n\u001b[32m 400\u001b[39m \u001b[33;03m Optimization is done by choosing a suitable set of hyperparameter values from a given\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 487\u001b[39m \u001b[33;03m If nested invocation of this method occurs.\u001b[39;00m\n\u001b[32m 488\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m489\u001b[39m \u001b[43m_optimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 490\u001b[39m \u001b[43m \u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 491\u001b[39m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 492\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 493\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 494\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 495\u001b[39m \u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mIterable\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 496\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 497\u001b[39m \u001b[43m \u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 498\u001b[39m \u001b[43m \u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 499\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:64\u001b[39m, in \u001b[36m_optimize\u001b[39m\u001b[34m(study, func, n_trials, timeout, n_jobs, catch, callbacks, gc_after_trial, show_progress_bar)\u001b[39m\n\u001b[32m 62\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 63\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m n_jobs == \u001b[32m1\u001b[39m:\n\u001b[32m---> \u001b[39m\u001b[32m64\u001b[39m \u001b[43m_optimize_sequential\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 65\u001b[39m \u001b[43m \u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 66\u001b[39m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 67\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 68\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 69\u001b[39m \u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 70\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 71\u001b[39m \u001b[43m \u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 72\u001b[39m \u001b[43m \u001b[49m\u001b[43mreseed_sampler_rng\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 73\u001b[39m \u001b[43m \u001b[49m\u001b[43mtime_start\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 74\u001b[39m \u001b[43m \u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 75\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 76\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 77\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m n_jobs == -\u001b[32m1\u001b[39m:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:161\u001b[39m, in \u001b[36m_optimize_sequential\u001b[39m\u001b[34m(study, func, n_trials, timeout, catch, callbacks, gc_after_trial, reseed_sampler_rng, time_start, progress_bar)\u001b[39m\n\u001b[32m 158\u001b[39m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[32m 160\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m161\u001b[39m frozen_trial = \u001b[43m_run_trial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 162\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 163\u001b[39m \u001b[38;5;66;03m# The following line mitigates memory problems that can be occurred in some\u001b[39;00m\n\u001b[32m 164\u001b[39m \u001b[38;5;66;03m# environments (e.g., services that use computing containers such as GitHub Actions).\u001b[39;00m\n\u001b[32m 165\u001b[39m \u001b[38;5;66;03m# Please refer to the following PR for further details:\u001b[39;00m\n\u001b[32m 166\u001b[39m \u001b[38;5;66;03m# https://github.com/optuna/optuna/pull/325.\u001b[39;00m\n\u001b[32m 167\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m gc_after_trial:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:253\u001b[39m, in \u001b[36m_run_trial\u001b[39m\u001b[34m(study, func, catch)\u001b[39m\n\u001b[32m 246\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[33m\"\u001b[39m\u001b[33mShould not reach.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 248\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[32m 249\u001b[39m frozen_trial.state == TrialState.FAIL\n\u001b[32m 250\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m func_err \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 251\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(func_err, catch)\n\u001b[32m 252\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m253\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m func_err\n\u001b[32m 254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m frozen_trial\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:201\u001b[39m, in \u001b[36m_run_trial\u001b[39m\u001b[34m(study, func, catch)\u001b[39m\n\u001b[32m 199\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m get_heartbeat_thread(trial._trial_id, study._storage):\n\u001b[32m 200\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m201\u001b[39m value_or_values = \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrial\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 202\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m exceptions.TrialPruned \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 203\u001b[39m \u001b[38;5;66;03m# TODO(mamu): Handle multi-objective cases.\u001b[39;00m\n\u001b[32m 204\u001b[39m state = TrialState.PRUNED\n", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 28\u001b[39m, in \u001b[36mobjective\u001b[39m\u001b[34m(trial)\u001b[39m\n\u001b[32m 5\u001b[39m params = {\n\u001b[32m 6\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mobjective\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mbinary\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 7\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmetric\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mbinary_logloss\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 23\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mverbosity\u001b[39m\u001b[33m\"\u001b[39m: -\u001b[32m1\u001b[39m,\n\u001b[32m 24\u001b[39m }\n\u001b[32m 26\u001b[39m model = lgb.LGBMClassifier(**params)\n\u001b[32m---> \u001b[39m\u001b[32m28\u001b[39m scores = \u001b[43mcross_val_score\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 29\u001b[39m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 30\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m=\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 31\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m=\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 32\u001b[39m \u001b[43m \u001b[49m\u001b[43mscoring\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mf1_weighted\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 33\u001b[39m \u001b[43m \u001b[49m\u001b[43mcv\u001b[49m\u001b[43m=\u001b[49m\u001b[43mStratifiedKFold\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_splits\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m10\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshuffle\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrandom_state\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m42\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 34\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 35\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 37\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores.mean()\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py:216\u001b[39m, in \u001b[36mvalidate_params..decorator..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 210\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 211\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 212\u001b[39m skip_parameter_validation=(\n\u001b[32m 213\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 214\u001b[39m )\n\u001b[32m 215\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m216\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 218\u001b[39m \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[32m 219\u001b[39m \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[32m 220\u001b[39m \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[32m 221\u001b[39m \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[32m 222\u001b[39m msg = re.sub(\n\u001b[32m 223\u001b[39m \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[33m\\\u001b[39m\u001b[33mw+ must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 224\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc.\u001b[34m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 225\u001b[39m \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[32m 226\u001b[39m )\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:684\u001b[39m, in \u001b[36mcross_val_score\u001b[39m\u001b[34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, params, pre_dispatch, error_score)\u001b[39m\n\u001b[32m 681\u001b[39m \u001b[38;5;66;03m# To ensure multimetric format is not supported\u001b[39;00m\n\u001b[32m 682\u001b[39m scorer = check_scoring(estimator, scoring=scoring)\n\u001b[32m--> \u001b[39m\u001b[32m684\u001b[39m cv_results = \u001b[43mcross_validate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 685\u001b[39m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m=\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 686\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m=\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 687\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m=\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 688\u001b[39m \u001b[43m \u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 689\u001b[39m \u001b[43m \u001b[49m\u001b[43mscoring\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mscore\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mscorer\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 690\u001b[39m \u001b[43m \u001b[49m\u001b[43mcv\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 691\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 692\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 693\u001b[39m \u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[43m=\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 694\u001b[39m \u001b[43m \u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 695\u001b[39m \u001b[43m \u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m=\u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 696\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 697\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cv_results[\u001b[33m\"\u001b[39m\u001b[33mtest_score\u001b[39m\u001b[33m\"\u001b[39m]\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py:216\u001b[39m, in \u001b[36mvalidate_params..decorator..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 210\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 211\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 212\u001b[39m skip_parameter_validation=(\n\u001b[32m 213\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 214\u001b[39m )\n\u001b[32m 215\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m216\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 218\u001b[39m \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[32m 219\u001b[39m \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[32m 220\u001b[39m \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[32m 221\u001b[39m \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[32m 222\u001b[39m msg = re.sub(\n\u001b[32m 223\u001b[39m \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[33m\\\u001b[39m\u001b[33mw+ must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 224\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc.\u001b[34m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 225\u001b[39m \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[32m 226\u001b[39m )\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:431\u001b[39m, in \u001b[36mcross_validate\u001b[39m\u001b[34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, params, pre_dispatch, return_train_score, return_estimator, return_indices, error_score)\u001b[39m\n\u001b[32m 410\u001b[39m parallel = Parallel(n_jobs=n_jobs, verbose=verbose, pre_dispatch=pre_dispatch)\n\u001b[32m 411\u001b[39m results = parallel(\n\u001b[32m 412\u001b[39m delayed(_fit_and_score)(\n\u001b[32m 413\u001b[39m clone(estimator),\n\u001b[32m (...)\u001b[39m\u001b[32m 428\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m train, test \u001b[38;5;129;01min\u001b[39;00m indices\n\u001b[32m 429\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m431\u001b[39m \u001b[43m_warn_or_raise_about_fit_failures\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresults\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 433\u001b[39m \u001b[38;5;66;03m# For callable scoring, the return type is only know after calling. If the\u001b[39;00m\n\u001b[32m 434\u001b[39m \u001b[38;5;66;03m# return type is a dictionary, the error scores can now be inserted with\u001b[39;00m\n\u001b[32m 435\u001b[39m \u001b[38;5;66;03m# the correct key.\u001b[39;00m\n\u001b[32m 436\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcallable\u001b[39m(scoring):\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:517\u001b[39m, in \u001b[36m_warn_or_raise_about_fit_failures\u001b[39m\u001b[34m(results, error_score)\u001b[39m\n\u001b[32m 510\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m num_failed_fits == num_fits:\n\u001b[32m 511\u001b[39m all_fits_failed_message = (\n\u001b[32m 512\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mAll the \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m fits failed.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 513\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mIt is very likely that your model is misconfigured.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 514\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mYou can try to debug the error by setting error_score=\u001b[39m\u001b[33m'\u001b[39m\u001b[33mraise\u001b[39m\u001b[33m'\u001b[39m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 515\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mBelow are more details about the failures:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mfit_errors_summary\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 516\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m517\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(all_fits_failed_message)\n\u001b[32m 519\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 520\u001b[39m some_fits_failed_message = (\n\u001b[32m 521\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mnum_failed_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m fits failed out of a total of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 522\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mThe score on these train-test partitions for these parameters\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m (...)\u001b[39m\u001b[32m 526\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mBelow are more details about the failures:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mfit_errors_summary\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 527\u001b[39m )\n", - "\u001b[31mValueError\u001b[39m: \nAll the 10 fits failed.\nIt is very likely that your model is misconfigured.\nYou can try to debug the error by setting error_score='raise'.\n\nBelow are more details about the failures:\n--------------------------------------------------------------------------------\n10 fits failed with the following error:\nTraceback (most recent call last):\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n estimator.fit(X_train, y_train, **fit_params)\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n super().fit(\n ~~~~~~~~~~~^\n X,\n ^^\n ...<12 lines>...\n init_model=init_model,\n ^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n self._Booster = train(\n ~~~~~^\n params=params,\n ^^^^^^^^^^^^^^\n ...<6 lines>...\n callbacks=callbacks,\n ^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n booster = Booster(params=params, train_set=train_set)\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n train_set.construct()\n ~~~~~~~~~~~~~~~~~~~^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n self._lazy_init(\n ~~~~~~~~~~~~~~~^\n data=self.data,\n ^^^^^^^^^^^^^^^\n ...<9 lines>...\n position=self.position,\n ^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n return self.set_feature_name(feature_name)\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n _safe_call(\n ~~~~~~~~~~^\n _LIB.LGBM_DatasetSetFeatureNames(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<3 lines>...\n )\n ^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n" - ] - } - ], - "source": [ - "import lightgbm as lgb\n", - "\n", - "\n", - "def objective(trial):\n", - " params = {\n", - " \"objective\": \"binary\",\n", - " \"metric\": \"binary_logloss\",\n", - " \"boosting_type\": trial.suggest_categorical(\n", - " \"boosting_type\", [\"gbdt\", \"dart\", \"goss\"]\n", - " ),\n", - " \"num_leaves\": trial.suggest_int(\"num_leaves\", 2, 256),\n", - " \"learning_rate\": trial.suggest_float(\"learning_rate\", 1e-3, 0.1, log=True),\n", - " \"n_estimators\": trial.suggest_int(\"n_estimators\", 20, 1000),\n", - " \"max_depth\": trial.suggest_int(\"max_depth\", 1, 20),\n", - " \"min_child_samples\": trial.suggest_int(\"min_child_samples\", 1, 100),\n", - " \"subsample\": trial.suggest_float(\"subsample\", 0.5, 1.0),\n", - " \"colsample_bytree\": trial.suggest_float(\"colsample_bytree\", 0.5, 1.0),\n", - " \"reg_alpha\": trial.suggest_float(\"reg_alpha\", 1e-8, 10.0, log=True),\n", - " \"reg_lambda\": trial.suggest_float(\"reg_lambda\", 1e-8, 10.0, log=True),\n", - " \"min_split_gain\": trial.suggest_float(\"min_split_gain\", 1e-8, 1.0, log=True),\n", - " \"cat_smooth\": trial.suggest_int(\"cat_smooth\", 1, 100),\n", - " \"cat_l2\": trial.suggest_float(\"cat_l2\", 1e-8, 10.0, log=True),\n", - " \"verbosity\": -1,\n", - " }\n", - "\n", - " model = lgb.LGBMClassifier(**params)\n", - "\n", - " scores = cross_val_score(\n", - " estimator=model,\n", - " X=X,\n", - " y=y,\n", - " scoring=\"f1_weighted\",\n", - " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", - " n_jobs=-1,\n", - " )\n", - "\n", - " return scores.mean()\n", - "\n", - "\n", - "study = optuna.create_study(direction=\"maximize\")\n", - "study.optimize(objective, n_trials=200)\n", - "\n", - "best_trial = study.best_trial\n", - "\n", - "print(\"Best trial:\")\n", - "print(f\"F1 Score: {best_trial.value:.6f}\")\n", - "print(\"Parameters:\")\n", - "for k, v in best_trial.params.items():\n", - " print(f\"{k}: {v}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**CatBoost results:**" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-18 23:04:37,538] A new study created in memory with name: no-name-a6ac08d4-0166-4e55-82db-e34c20f65e38\n", + "[I 2025-08-18 23:04:38,723] Trial 0 finished with value: 0.9636743691091517 and parameters: {'n_estimators': 793, 'max_depth': 16, 'learning_rate': 0.08966826500844771, 'gamma': 1.5332174950801975e-05, 'min_child_weight': 7, 'subsample': 0.8206767596857434, 'colsample_bytree': 0.5726809729609164, 'reg_alpha': 0.3000662922036043, 'reg_lambda': 6.694076855447791e-06}. Best is trial 0 with value: 0.9636743691091517.\n", + "[I 2025-08-18 23:04:39,297] Trial 1 finished with value: 0.92515962298571 and parameters: {'n_estimators': 363, 'max_depth': 1, 'learning_rate': 0.6923884519284504, 'gamma': 2.3719556857557514e-07, 'min_child_weight': 9, 'subsample': 0.5195696271131344, 'colsample_bytree': 0.9721890311504119, 'reg_alpha': 0.0004982860931446735, 'reg_lambda': 4.9598622967800296e-08}. Best is trial 0 with value: 0.9636743691091517.\n", + "[I 2025-08-18 23:04:39,907] Trial 2 finished with value: 0.9660813823857302 and parameters: {'n_estimators': 765, 'max_depth': 19, 'learning_rate': 0.03328962689146766, 'gamma': 0.005416426649707568, 'min_child_weight': 5, 'subsample': 0.8716669106394426, 'colsample_bytree': 0.619605690338052, 'reg_alpha': 0.1588033011486252, 'reg_lambda': 0.10090421373216449}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:39,956] Trial 3 finished with value: 0.9646701124961995 and parameters: {'n_estimators': 162, 'max_depth': 14, 'learning_rate': 0.22096268147375914, 'gamma': 0.20303915469434114, 'min_child_weight': 3, 'subsample': 0.7816550027087239, 'colsample_bytree': 0.9440324292952285, 'reg_alpha': 0.00019615793084263862, 'reg_lambda': 0.00012620616546111783}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,531] Trial 4 finished with value: 0.9618906455862977 and parameters: {'n_estimators': 746, 'max_depth': 5, 'learning_rate': 0.27373124279594174, 'gamma': 5.113866726169806e-07, 'min_child_weight': 8, 'subsample': 0.9786346051499656, 'colsample_bytree': 0.817382203507034, 'reg_alpha': 0.00010865601540579662, 'reg_lambda': 0.7028348077651659}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,571] Trial 5 finished with value: 0.9375772777946689 and parameters: {'n_estimators': 131, 'max_depth': 9, 'learning_rate': 0.6666830358877334, 'gamma': 2.3337802367945706e-06, 'min_child_weight': 10, 'subsample': 0.5767815340215819, 'colsample_bytree': 0.8847564080638974, 'reg_alpha': 1.1720116806607218e-05, 'reg_lambda': 0.00014985518222546636}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,647] Trial 6 finished with value: 0.9322793148880105 and parameters: {'n_estimators': 811, 'max_depth': 19, 'learning_rate': 0.6284423078537571, 'gamma': 2.5468120149201276e-08, 'min_child_weight': 8, 'subsample': 0.5241240142259422, 'colsample_bytree': 0.7077124133325703, 'reg_alpha': 0.00122899449385656, 'reg_lambda': 4.150700737033019e-05}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,675] Trial 7 finished with value: 0.9404048849701023 and parameters: {'n_estimators': 55, 'max_depth': 8, 'learning_rate': 0.6143004867698488, 'gamma': 0.0013027026334781191, 'min_child_weight': 7, 'subsample': 0.6231620588280503, 'colsample_bytree': 0.8828670937564691, 'reg_alpha': 2.9404686235297146e-07, 'reg_lambda': 3.754444639692557e-06}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,740] Trial 8 finished with value: 0.9578595317725753 and parameters: {'n_estimators': 499, 'max_depth': 18, 'learning_rate': 0.5646291569978734, 'gamma': 1.7349709546981462e-05, 'min_child_weight': 2, 'subsample': 0.8928178421726397, 'colsample_bytree': 0.6848598778618181, 'reg_alpha': 0.5610745294606653, 'reg_lambda': 0.5364150960157834}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,805] Trial 9 finished with value: 0.9590174318435187 and parameters: {'n_estimators': 699, 'max_depth': 4, 'learning_rate': 0.31764392327897784, 'gamma': 0.11453542510872944, 'min_child_weight': 10, 'subsample': 0.7055074511257982, 'colsample_bytree': 0.796546556661627, 'reg_alpha': 2.907763331398582e-05, 'reg_lambda': 2.2504856133119337e-05}. Best is trial 2 with value: 0.9660813823857302.\n", + "[I 2025-08-18 23:04:40,963] Trial 10 finished with value: 0.9670897942637072 and parameters: {'n_estimators': 972, 'max_depth': 13, 'learning_rate': 0.02160073099534278, 'gamma': 0.0012263645582748532, 'min_child_weight': 4, 'subsample': 0.9792412216883989, 'colsample_bytree': 0.520612587086734, 'reg_alpha': 0.013660705792304169, 'reg_lambda': 0.011791232435673288}. Best is trial 10 with value: 0.9670897942637072.\n", + "[I 2025-08-18 23:04:41,107] Trial 11 finished with value: 0.9643077936556198 and parameters: {'n_estimators': 950, 'max_depth': 12, 'learning_rate': 0.02786001957318099, 'gamma': 0.0017314307200539348, 'min_child_weight': 4, 'subsample': 0.9907050379036834, 'colsample_bytree': 0.5125919786788546, 'reg_alpha': 0.01547481122556199, 'reg_lambda': 0.021894838205846742}. Best is trial 10 with value: 0.9670897942637072.\n", + "[I 2025-08-18 23:04:41,213] Trial 12 finished with value: 0.9663930272625926 and parameters: {'n_estimators': 993, 'max_depth': 20, 'learning_rate': 0.14543560489328874, 'gamma': 0.0033996503304433074, 'min_child_weight': 5, 'subsample': 0.8889007946941537, 'colsample_bytree': 0.6084715786342512, 'reg_alpha': 0.022413404033686066, 'reg_lambda': 0.011064527798418372}. Best is trial 10 with value: 0.9670897942637072.\n", + "[I 2025-08-18 23:04:41,322] Trial 13 finished with value: 0.968164082294517 and parameters: {'n_estimators': 955, 'max_depth': 14, 'learning_rate': 0.1639284511998979, 'gamma': 0.0002751891194586191, 'min_child_weight': 1, 'subsample': 0.9147497384875082, 'colsample_bytree': 0.5126649768955113, 'reg_alpha': 0.016597036392593374, 'reg_lambda': 0.004707104171200651}. Best is trial 13 with value: 0.968164082294517.\n", + "[I 2025-08-18 23:04:41,408] Trial 14 finished with value: 0.9720735785953177 and parameters: {'n_estimators': 635, 'max_depth': 12, 'learning_rate': 0.44435309051067096, 'gamma': 0.0006644642045654169, 'min_child_weight': 1, 'subsample': 0.9432618865143836, 'colsample_bytree': 0.5039154540738406, 'reg_alpha': 0.004876635115949546, 'reg_lambda': 0.0064355512337324105}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,484] Trial 15 finished with value: 0.9674521131042871 and parameters: {'n_estimators': 569, 'max_depth': 10, 'learning_rate': 0.43787269752034375, 'gamma': 0.00011195314945572638, 'min_child_weight': 1, 'subsample': 0.7069629644516782, 'colsample_bytree': 0.5634075101229923, 'reg_alpha': 4.464784207396974e-08, 'reg_lambda': 0.003997182136400165}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,558] Trial 16 finished with value: 0.9707433870477349 and parameters: {'n_estimators': 370, 'max_depth': 15, 'learning_rate': 0.4599427117745171, 'gamma': 8.735091706299628e-05, 'min_child_weight': 1, 'subsample': 0.9257669635457493, 'colsample_bytree': 0.6689607583849055, 'reg_alpha': 0.003005669831594476, 'reg_lambda': 0.0009691828324956179}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,631] Trial 17 finished with value: 0.9679563190432756 and parameters: {'n_estimators': 336, 'max_depth': 16, 'learning_rate': 0.4272808911789559, 'gamma': 1.1267461214053029e-05, 'min_child_weight': 2, 'subsample': 0.8380523208836226, 'colsample_bytree': 0.672358753892155, 'reg_alpha': 3.5941246015085105e-06, 'reg_lambda': 0.0012762246601831144}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,703] Trial 18 finished with value: 0.962460727678119 and parameters: {'n_estimators': 412, 'max_depth': 7, 'learning_rate': 0.4945841962092967, 'gamma': 0.7046722512199631, 'min_child_weight': 2, 'subsample': 0.9443084841264685, 'colsample_bytree': 0.752150502842086, 'reg_alpha': 0.0022930157034841687, 'reg_lambda': 0.0005914759736460705}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,781] Trial 19 finished with value: 0.9693523867436911 and parameters: {'n_estimators': 603, 'max_depth': 11, 'learning_rate': 0.4182386109054242, 'gamma': 0.02844656967423761, 'min_child_weight': 3, 'subsample': 0.7636043135868457, 'colsample_bytree': 0.6293491016063527, 'reg_alpha': 0.002891811181173915, 'reg_lambda': 6.079751271976952e-07}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,844] Trial 20 finished with value: 0.9646321070234114 and parameters: {'n_estimators': 263, 'max_depth': 16, 'learning_rate': 0.5343710663782837, 'gamma': 0.00020994204354847013, 'min_child_weight': 1, 'subsample': 0.933551117358393, 'colsample_bytree': 0.7553892763360576, 'reg_alpha': 1.4227453672543946e-06, 'reg_lambda': 0.07295757354368651}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:41,929] Trial 21 finished with value: 0.9683287726765988 and parameters: {'n_estimators': 618, 'max_depth': 11, 'learning_rate': 0.39203875257523096, 'gamma': 0.020660444962692592, 'min_child_weight': 3, 'subsample': 0.7522258388072962, 'colsample_bytree': 0.6287497031716449, 'reg_alpha': 0.0027780793331277473, 'reg_lambda': 4.744211463091777e-07}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,003] Trial 22 finished with value: 0.9650729705077531 and parameters: {'n_estimators': 479, 'max_depth': 11, 'learning_rate': 0.4816697063234048, 'gamma': 0.02294520899250463, 'min_child_weight': 3, 'subsample': 0.8261862173185567, 'colsample_bytree': 0.6535905438209455, 'reg_alpha': 0.05648104038500446, 'reg_lambda': 7.945709365351044e-08}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,087] Trial 23 finished with value: 0.9649690888821322 and parameters: {'n_estimators': 617, 'max_depth': 14, 'learning_rate': 0.35399121863614574, 'gamma': 0.023886459668739847, 'min_child_weight': 1, 'subsample': 0.6707746880436944, 'colsample_bytree': 0.5755080172718738, 'reg_alpha': 0.004076372892245553, 'reg_lambda': 9.163582970819522e-07}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,163] Trial 24 finished with value: 0.9611761426978817 and parameters: {'n_estimators': 443, 'max_depth': 12, 'learning_rate': 0.3139681715812469, 'gamma': 0.0003768107966552948, 'min_child_weight': 2, 'subsample': 0.785577063811775, 'colsample_bytree': 0.7035064694391241, 'reg_alpha': 0.0002961952288355031, 'reg_lambda': 0.0007189349722448769}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,226] Trial 25 finished with value: 0.9621769534813012 and parameters: {'n_estimators': 270, 'max_depth': 17, 'learning_rate': 0.46661524082093503, 'gamma': 3.724723823557411e-05, 'min_child_weight': 4, 'subsample': 0.8543235968447394, 'colsample_bytree': 0.5745613732539564, 'reg_alpha': 5.043186797452251e-05, 'reg_lambda': 1.0823805710576936e-08}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,310] Trial 26 finished with value: 0.967454646802473 and parameters: {'n_estimators': 571, 'max_depth': 7, 'learning_rate': 0.39555431045443845, 'gamma': 0.010531397617842813, 'min_child_weight': 3, 'subsample': 0.9520895450331223, 'colsample_bytree': 0.6505146452181498, 'reg_alpha': 0.07277660854823283, 'reg_lambda': 0.00017848811714192225}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,407] Trial 27 finished with value: 0.971115840681058 and parameters: {'n_estimators': 886, 'max_depth': 15, 'learning_rate': 0.5596905359749961, 'gamma': 0.109957517842398, 'min_child_weight': 1, 'subsample': 0.911463740843732, 'colsample_bytree': 0.7242482520459889, 'reg_alpha': 0.004304571005570774, 'reg_lambda': 0.0019289290476947067}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,567] Trial 28 finished with value: 0.9622124252559034 and parameters: {'n_estimators': 856, 'max_depth': 15, 'learning_rate': 0.5491779113793174, 'gamma': 0.9394863827667955, 'min_child_weight': 1, 'subsample': 0.9085194590375377, 'colsample_bytree': 0.8008991430166865, 'reg_alpha': 0.0007901559140269053, 'reg_lambda': 0.0017254433653291876}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,670] Trial 29 finished with value: 0.9647359886490323 and parameters: {'n_estimators': 862, 'max_depth': 17, 'learning_rate': 0.5820996718221064, 'gamma': 5.022199051728779e-06, 'min_child_weight': 6, 'subsample': 0.8071126403433657, 'colsample_bytree': 0.8688765430232145, 'reg_alpha': 0.6743398600163427, 'reg_lambda': 0.07862706605671561}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,758] Trial 30 finished with value: 0.9642292490118578 and parameters: {'n_estimators': 709, 'max_depth': 13, 'learning_rate': 0.5155202664068682, 'gamma': 5.8451733953677565e-05, 'min_child_weight': 2, 'subsample': 0.9509763250842893, 'colsample_bytree': 0.7129940865613236, 'reg_alpha': 0.008859259561073272, 'reg_lambda': 3.4509898100450316e-05}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,845] Trial 31 finished with value: 0.9657722712070538 and parameters: {'n_estimators': 668, 'max_depth': 10, 'learning_rate': 0.4395334552771406, 'gamma': 0.12712718293414763, 'min_child_weight': 1, 'subsample': 0.9988158980266512, 'colsample_bytree': 0.5936405830531623, 'reg_alpha': 0.004952419311036929, 'reg_lambda': 6.401818643223202e-06}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,919] Trial 32 finished with value: 0.961406709232796 and parameters: {'n_estimators': 566, 'max_depth': 15, 'learning_rate': 0.3597185445003348, 'gamma': 0.052315813645452125, 'min_child_weight': 2, 'subsample': 0.861533388856762, 'colsample_bytree': 0.5482756215722395, 'reg_alpha': 0.0008797977184427369, 'reg_lambda': 0.000414443174592793}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:42,983] Trial 33 finished with value: 0.9657722712070539 and parameters: {'n_estimators': 356, 'max_depth': 12, 'learning_rate': 0.5063187891048766, 'gamma': 0.0006293033474033146, 'min_child_weight': 3, 'subsample': 0.9245516224148534, 'colsample_bytree': 0.7700173552170951, 'reg_alpha': 0.1375518302261409, 'reg_lambda': 0.0033261674432578194}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,056] Trial 34 finished with value: 0.9628433161041858 and parameters: {'n_estimators': 281, 'max_depth': 15, 'learning_rate': 0.39986529526862014, 'gamma': 0.33270406488078025, 'min_child_weight': 1, 'subsample': 0.8777255486034471, 'colsample_bytree': 0.6377133084935319, 'reg_alpha': 0.00040666270333044826, 'reg_lambda': 0.01722992299278233}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,143] Trial 35 finished with value: 0.9677789601702645 and parameters: {'n_estimators': 809, 'max_depth': 13, 'learning_rate': 0.5932469392267316, 'gamma': 0.006088499877130821, 'min_child_weight': 2, 'subsample': 0.7328484494819534, 'colsample_bytree': 0.7319378460341505, 'reg_alpha': 0.05604671729670822, 'reg_lambda': 0.00026653903767523407}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,242] Trial 36 finished with value: 0.9578975372453634 and parameters: {'n_estimators': 894, 'max_depth': 17, 'learning_rate': 0.6747312199854105, 'gamma': 1.4778405111109977e-06, 'min_child_weight': 4, 'subsample': 0.8061783788836056, 'colsample_bytree': 0.6785763400584698, 'reg_alpha': 0.00011687995768555662, 'reg_lambda': 0.23451609747860863}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,305] Trial 37 finished with value: 0.9607327455153543 and parameters: {'n_estimators': 416, 'max_depth': 1, 'learning_rate': 0.4620319359751538, 'gamma': 0.060081915589133755, 'min_child_weight': 3, 'subsample': 0.9671673389437769, 'colsample_bytree': 0.5439077141472997, 'reg_alpha': 0.0016050980147079938, 'reg_lambda': 0.03470161515812803}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,391] Trial 38 finished with value: 0.9623315090706395 and parameters: {'n_estimators': 741, 'max_depth': 9, 'learning_rate': 0.26537466239492763, 'gamma': 3.8588922199082426e-08, 'min_child_weight': 6, 'subsample': 0.6229188943554498, 'colsample_bytree': 0.8482038406619968, 'reg_alpha': 0.005961031499798193, 'reg_lambda': 9.178673123098809e-05}. Best is trial 14 with value: 0.9720735785953177.\n", + "[I 2025-08-18 23:04:43,453] Trial 39 finished with value: 0.9733835005574136 and parameters: {'n_estimators': 174, 'max_depth': 9, 'learning_rate': 0.3415861867273047, 'gamma': 0.00320158129516171, 'min_child_weight': 1, 'subsample': 0.7657875222614208, 'colsample_bytree': 0.6055391800615106, 'reg_alpha': 0.1961144247885326, 'reg_lambda': 1.3349872128243998e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,528] Trial 40 finished with value: 0.968103273538056 and parameters: {'n_estimators': 194, 'max_depth': 5, 'learning_rate': 0.2308941510629727, 'gamma': 0.002267995615949968, 'min_child_weight': 1, 'subsample': 0.907878075061457, 'colsample_bytree': 0.9968707460456452, 'reg_alpha': 0.18618906668818894, 'reg_lambda': 1.9657102325946478e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,569] Trial 41 finished with value: 0.9706876456876458 and parameters: {'n_estimators': 26, 'max_depth': 9, 'learning_rate': 0.3394366537016498, 'gamma': 0.0075177253863414695, 'min_child_weight': 2, 'subsample': 0.7720455412614378, 'colsample_bytree': 0.607113034664798, 'reg_alpha': 0.02755418326100873, 'reg_lambda': 1.6417879593738852e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,622] Trial 42 finished with value: 0.9656278504104592 and parameters: {'n_estimators': 28, 'max_depth': 8, 'learning_rate': 0.3375467490973728, 'gamma': 0.008183578589292693, 'min_child_weight': 2, 'subsample': 0.7841595414778176, 'colsample_bytree': 0.6001413581900443, 'reg_alpha': 0.039635394071934116, 'reg_lambda': 1.820175490207568e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,686] Trial 43 finished with value: 0.9674166413296849 and parameters: {'n_estimators': 92, 'max_depth': 9, 'learning_rate': 0.2951892312329311, 'gamma': 0.0011926871557951385, 'min_child_weight': 1, 'subsample': 0.7243233789331518, 'colsample_bytree': 0.6690830197165509, 'reg_alpha': 0.2981096546445941, 'reg_lambda': 1.4732474336111884e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,737] Trial 44 finished with value: 0.9664665045099827 and parameters: {'n_estimators': 176, 'max_depth': 3, 'learning_rate': 0.3778692466816108, 'gamma': 0.0006795734196391805, 'min_child_weight': 2, 'subsample': 0.846170946192214, 'colsample_bytree': 0.5421093232735782, 'reg_alpha': 0.1171370589737971, 'reg_lambda': 9.218742520129267e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,790] Trial 45 finished with value: 0.9642292490118578 and parameters: {'n_estimators': 112, 'max_depth': 6, 'learning_rate': 0.26260487033994784, 'gamma': 0.00011851832743201036, 'min_child_weight': 1, 'subsample': 0.670336459772904, 'colsample_bytree': 0.7208950473295055, 'reg_alpha': 0.02908781781480345, 'reg_lambda': 6.543787850283628e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,852] Trial 46 finished with value: 0.96029948312557 and parameters: {'n_estimators': 220, 'max_depth': 9, 'learning_rate': 0.6312256464453558, 'gamma': 0.0036712637572776517, 'min_child_weight': 1, 'subsample': 0.8759520439984964, 'colsample_bytree': 0.6914986554072519, 'reg_alpha': 0.3474285764344179, 'reg_lambda': 0.006752518206121544}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,904] Trial 47 finished with value: 0.9499163879598662 and parameters: {'n_estimators': 146, 'max_depth': 19, 'learning_rate': 0.20922691721035272, 'gamma': 3.8419590657259207e-05, 'min_child_weight': 8, 'subsample': 0.5049535044393377, 'colsample_bytree': 0.9226368889131558, 'reg_alpha': 0.010213751761400837, 'reg_lambda': 0.0014363034008709101}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:43,969] Trial 48 finished with value: 0.9649412182020877 and parameters: {'n_estimators': 64, 'max_depth': 8, 'learning_rate': 0.07577872858481222, 'gamma': 0.2638175764876564, 'min_child_weight': 2, 'subsample': 0.963968884483731, 'colsample_bytree': 0.5924098530493901, 'reg_alpha': 0.999637524746841, 'reg_lambda': 2.0261391177441924e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,033] Trial 49 finished with value: 0.9655645079558124 and parameters: {'n_estimators': 318, 'max_depth': 14, 'learning_rate': 0.33052174325673006, 'gamma': 0.011942467037248633, 'min_child_weight': 1, 'subsample': 0.6627788600351412, 'colsample_bytree': 0.6141066675957493, 'reg_alpha': 0.021696432447302145, 'reg_lambda': 1.0007983816416382e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,088] Trial 50 finished with value: 0.9663803587716633 and parameters: {'n_estimators': 236, 'max_depth': 10, 'learning_rate': 0.45078154977126994, 'gamma': 1.5117023515346045e-05, 'min_child_weight': 2, 'subsample': 0.5688408997309418, 'colsample_bytree': 0.5299284944128524, 'reg_alpha': 1.8494068989589203e-08, 'reg_lambda': 0.0022820773871882346}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,161] Trial 51 finished with value: 0.9703557312252965 and parameters: {'n_estimators': 512, 'max_depth': 11, 'learning_rate': 0.5295370440664156, 'gamma': 0.06319050293389655, 'min_child_weight': 3, 'subsample': 0.7545681529668761, 'colsample_bytree': 0.6317023972454394, 'reg_alpha': 0.0015414355079223494, 'reg_lambda': 4.324091704580854e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,237] Trial 52 finished with value: 0.9709663524880916 and parameters: {'n_estimators': 514, 'max_depth': 12, 'learning_rate': 0.5300714512293007, 'gamma': 0.06686213254636227, 'min_child_weight': 2, 'subsample': 0.7598964166427791, 'colsample_bytree': 0.6527821461167355, 'reg_alpha': 0.0007257680068320631, 'reg_lambda': 2.053211374630651e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,301] Trial 53 finished with value: 0.9352690787473396 and parameters: {'n_estimators': 506, 'max_depth': 12, 'learning_rate': 0.571256600848416, 'gamma': 0.004555999545517148, 'min_child_weight': 9, 'subsample': 0.7047240133608822, 'colsample_bytree': 0.5018984188314298, 'reg_alpha': 0.0005907798905113109, 'reg_lambda': 2.4734342938311394e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,375] Trial 54 finished with value: 0.9644775514340731 and parameters: {'n_estimators': 395, 'max_depth': 13, 'learning_rate': 0.6124317734833269, 'gamma': 0.00048108720311051555, 'min_child_weight': 1, 'subsample': 0.7718507840031281, 'colsample_bytree': 0.6489094093412939, 'reg_alpha': 0.00010645026093228777, 'reg_lambda': 3.4160412117423306e-08}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,451] Trial 55 finished with value: 0.9688887199756765 and parameters: {'n_estimators': 463, 'max_depth': 18, 'learning_rate': 0.4202773904272926, 'gamma': 0.12392807749675176, 'min_child_weight': 2, 'subsample': 0.8134953557614573, 'colsample_bytree': 0.5607537502942631, 'reg_alpha': 0.00023820341543495421, 'reg_lambda': 2.1461245433286342e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,541] Trial 56 finished with value: 0.9663702239789196 and parameters: {'n_estimators': 669, 'max_depth': 10, 'learning_rate': 0.48574283632282905, 'gamma': 0.4148692898234699, 'min_child_weight': 1, 'subsample': 0.7307151250713312, 'colsample_bytree': 0.6678470212859086, 'reg_alpha': 0.008252969517073406, 'reg_lambda': 1.1251409603467727e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,616] Trial 57 finished with value: 0.9625139353400222 and parameters: {'n_estimators': 525, 'max_depth': 7, 'learning_rate': 0.5519120903294772, 'gamma': 0.0001874680975299932, 'min_child_weight': 5, 'subsample': 0.8900352044342466, 'colsample_bytree': 0.6932159225648519, 'reg_alpha': 0.002517108855212675, 'reg_lambda': 4.297366901491959e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,682] Trial 58 finished with value: 0.966405695753522 and parameters: {'n_estimators': 306, 'max_depth': 15, 'learning_rate': 0.3674085407668765, 'gamma': 0.0017976084371012489, 'min_child_weight': 2, 'subsample': 0.824737146000951, 'colsample_bytree': 0.7399794252049822, 'reg_alpha': 0.015847378796743628, 'reg_lambda': 0.0005358852795940928}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,783] Trial 59 finished with value: 0.9697856491334752 and parameters: {'n_estimators': 774, 'max_depth': 13, 'learning_rate': 0.6457443852498842, 'gamma': 0.012496329388736885, 'min_child_weight': 1, 'subsample': 0.793838230860561, 'colsample_bytree': 0.5836425111317189, 'reg_alpha': 2.1754437677486564e-05, 'reg_lambda': 0.03337705451236421}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,846] Trial 60 finished with value: 0.963887199756765 and parameters: {'n_estimators': 382, 'max_depth': 12, 'learning_rate': 0.47328611057555103, 'gamma': 0.0424604798937201, 'min_child_weight': 4, 'subsample': 0.934552791164968, 'colsample_bytree': 0.7790054412552747, 'reg_alpha': 0.0011101990270547515, 'reg_lambda': 1.6827865084742688e-05}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,925] Trial 61 finished with value: 0.9660205736292694 and parameters: {'n_estimators': 545, 'max_depth': 11, 'learning_rate': 0.5055055462729076, 'gamma': 0.18056516452373952, 'min_child_weight': 3, 'subsample': 0.7519924075640182, 'colsample_bytree': 0.6178207309513841, 'reg_alpha': 0.0020172691789128233, 'reg_lambda': 3.9215049717299714e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:44,998] Trial 62 finished with value: 0.9557236242018851 and parameters: {'n_estimators': 473, 'max_depth': 11, 'learning_rate': 0.5400019943938102, 'gamma': 0.07754945232934854, 'min_child_weight': 2, 'subsample': 0.691256641899452, 'colsample_bytree': 0.6416326406060736, 'reg_alpha': 0.003532251580912962, 'reg_lambda': 1.0910716788302746e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,075] Trial 63 finished with value: 0.9659648322691801 and parameters: {'n_estimators': 640, 'max_depth': 10, 'learning_rate': 0.5246673195092458, 'gamma': 0.017184255393415157, 'min_child_weight': 1, 'subsample': 0.7639435627387441, 'colsample_bytree': 0.660278919577028, 'reg_alpha': 0.0005455413550718301, 'reg_lambda': 1.917088427074494e-08}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,139] Trial 64 finished with value: 0.964343265430222 and parameters: {'n_estimators': 442, 'max_depth': 14, 'learning_rate': 0.6003911375434905, 'gamma': 0.037188909985777056, 'min_child_weight': 3, 'subsample': 0.8347898516250483, 'colsample_bytree': 0.6269187811627178, 'reg_alpha': 0.0011552312420663807, 'reg_lambda': 2.833228903339653e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,180] Trial 65 finished with value: 0.9688912536738623 and parameters: {'n_estimators': 27, 'max_depth': 16, 'learning_rate': 0.2882497364553881, 'gamma': 0.0009365344901339396, 'min_child_weight': 2, 'subsample': 0.7470376879442628, 'colsample_bytree': 0.7041041755942481, 'reg_alpha': 0.08121948743500555, 'reg_lambda': 5.089309275914002e-08}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,281] Trial 66 finished with value: 0.9698261883044491 and parameters: {'n_estimators': 580, 'max_depth': 9, 'learning_rate': 0.4159616356940845, 'gamma': 0.5831219162124316, 'min_child_weight': 1, 'subsample': 0.982382322395441, 'colsample_bytree': 0.6102710521767731, 'reg_alpha': 0.0059321708676018815, 'reg_lambda': 0.005835785017549864}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,358] Trial 67 finished with value: 0.9618602412080672 and parameters: {'n_estimators': 534, 'max_depth': 8, 'learning_rate': 0.5710556707328297, 'gamma': 0.09669043321056411, 'min_child_weight': 3, 'subsample': 0.9073873458628307, 'colsample_bytree': 0.6799121381784294, 'reg_alpha': 0.0363553592541077, 'reg_lambda': 0.0010027836004984157}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,457] Trial 68 finished with value: 0.967196209587514 and parameters: {'n_estimators': 936, 'max_depth': 12, 'learning_rate': 0.49474283126858015, 'gamma': 0.0038977451885714052, 'min_child_weight': 2, 'subsample': 0.718024396773361, 'colsample_bytree': 0.5552789770779454, 'reg_alpha': 0.00037830643324867133, 'reg_lambda': 1.1088488335267902e-06}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,510] Trial 69 finished with value: 0.955052194182629 and parameters: {'n_estimators': 113, 'max_depth': 14, 'learning_rate': 0.5265511334361885, 'gamma': 0.002516218958369442, 'min_child_weight': 1, 'subsample': 0.7984530114493523, 'colsample_bytree': 0.7246949533111133, 'reg_alpha': 0.009898780192040475, 'reg_lambda': 0.0002248622535206601}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,573] Trial 70 finished with value: 0.9673761021587108 and parameters: {'n_estimators': 361, 'max_depth': 11, 'learning_rate': 0.4500338383720486, 'gamma': 7.97419217113888e-05, 'min_child_weight': 1, 'subsample': 0.7758735699887569, 'colsample_bytree': 0.6353171405510678, 'reg_alpha': 0.003990138744326455, 'reg_lambda': 6.367408215373258e-07}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,661] Trial 71 finished with value: 0.9699883449883451 and parameters: {'n_estimators': 574, 'max_depth': 9, 'learning_rate': 0.39331230829103997, 'gamma': 0.5832162124136367, 'min_child_weight': 1, 'subsample': 0.9892047975972974, 'colsample_bytree': 0.6070149608820187, 'reg_alpha': 0.005905898119536387, 'reg_lambda': 0.006704882688681093}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,747] Trial 72 finished with value: 0.9688507145028884 and parameters: {'n_estimators': 499, 'max_depth': 7, 'learning_rate': 0.38244445432292384, 'gamma': 0.18146664800759046, 'min_child_weight': 2, 'subsample': 0.9596340961165732, 'colsample_bytree': 0.572044864462482, 'reg_alpha': 0.016134020929382414, 'reg_lambda': 0.01234831939559891}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,846] Trial 73 finished with value: 0.9730591871896219 and parameters: {'n_estimators': 604, 'max_depth': 9, 'learning_rate': 0.3523875117331137, 'gamma': 0.5869038873091967, 'min_child_weight': 1, 'subsample': 0.9973259663877005, 'colsample_bytree': 0.6032453080408623, 'reg_alpha': 0.0022034163758147033, 'reg_lambda': 0.003049196789395216}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:45,943] Trial 74 finished with value: 0.9726867335562988 and parameters: {'n_estimators': 643, 'max_depth': 10, 'learning_rate': 0.3115429292430983, 'gamma': 0.036960550625807345, 'min_child_weight': 1, 'subsample': 0.9228507492640425, 'colsample_bytree': 0.5847404975899988, 'reg_alpha': 0.0014779764401295955, 'reg_lambda': 0.003412426872991884}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:46,042] Trial 75 finished with value: 0.9674419783115435 and parameters: {'n_estimators': 736, 'max_depth': 6, 'learning_rate': 0.31250026585052976, 'gamma': 0.00702536125685206, 'min_child_weight': 1, 'subsample': 0.9354922617992198, 'colsample_bytree': 0.5904428924919242, 'reg_alpha': 0.00019799922342255818, 'reg_lambda': 0.002649876404494166}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:46,140] Trial 76 finished with value: 0.96846305868045 and parameters: {'n_estimators': 662, 'max_depth': 10, 'learning_rate': 0.3376390484742646, 'gamma': 0.17746602873003298, 'min_child_weight': 1, 'subsample': 0.9210632567481764, 'colsample_bytree': 0.531169103386247, 'reg_alpha': 5.299213937151595e-05, 'reg_lambda': 0.0003542587698556304}. Best is trial 39 with value: 0.9733835005574136.\n", + "[I 2025-08-18 23:04:46,242] Trial 77 finished with value: 0.9755472788081484 and parameters: {'n_estimators': 699, 'max_depth': 8, 'learning_rate': 0.3024552441518453, 'gamma': 0.031847215034954184, 'min_child_weight': 1, 'subsample': 0.9453725012935073, 'colsample_bytree': 0.5761387875938053, 'reg_alpha': 0.002617366611378274, 'reg_lambda': 0.0010349784161099026}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,342] Trial 78 finished with value: 0.9712754636667679 and parameters: {'n_estimators': 710, 'max_depth': 16, 'learning_rate': 0.2782864761065816, 'gamma': 0.025218929923798795, 'min_child_weight': 1, 'subsample': 0.9452026017018716, 'colsample_bytree': 0.5742454517084862, 'reg_alpha': 0.0007904896535609112, 'reg_lambda': 0.0010678161736113964}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,439] Trial 79 finished with value: 0.9720355731225296 and parameters: {'n_estimators': 705, 'max_depth': 8, 'learning_rate': 0.24162738268963288, 'gamma': 0.03242084611379141, 'min_child_weight': 1, 'subsample': 0.9990849392959138, 'colsample_bytree': 0.5707898574308613, 'reg_alpha': 0.0007599244448927335, 'reg_lambda': 0.000865693881036213}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,540] Trial 80 finished with value: 0.9663651565825478 and parameters: {'n_estimators': 715, 'max_depth': 8, 'learning_rate': 0.2321298214642324, 'gamma': 0.03022699849641668, 'min_child_weight': 1, 'subsample': 0.9755760553478194, 'colsample_bytree': 0.5183018267013588, 'reg_alpha': 7.536762919465367e-06, 'reg_lambda': 0.0008972684138130091}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,634] Trial 81 finished with value: 0.9711842505320767 and parameters: {'n_estimators': 611, 'max_depth': 6, 'learning_rate': 0.202585095609433, 'gamma': 0.015614516083160477, 'min_child_weight': 1, 'subsample': 0.9438468399025172, 'colsample_bytree': 0.5749914104204584, 'reg_alpha': 0.0007169577786597087, 'reg_lambda': 0.003665927983254753}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,722] Trial 82 finished with value: 0.9691876963616094 and parameters: {'n_estimators': 609, 'max_depth': 6, 'learning_rate': 0.1869983439603146, 'gamma': 0.017565215748102506, 'min_child_weight': 1, 'subsample': 0.9986384186074727, 'colsample_bytree': 0.5694324397593564, 'reg_alpha': 0.0018715550848706019, 'reg_lambda': 0.0038007089962539624}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,829] Trial 83 finished with value: 0.9702011756359583 and parameters: {'n_estimators': 690, 'max_depth': 5, 'learning_rate': 0.15378234192456952, 'gamma': 0.026585421213008446, 'min_child_weight': 1, 'subsample': 0.9471578642997183, 'colsample_bytree': 0.5770861818398159, 'reg_alpha': 0.00014343058886510785, 'reg_lambda': 0.0015367425711003662}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:46,921] Trial 84 finished with value: 0.9754687341643864 and parameters: {'n_estimators': 639, 'max_depth': 4, 'learning_rate': 0.2487735126244442, 'gamma': 0.013668381092022869, 'min_child_weight': 1, 'subsample': 0.9738876470197214, 'colsample_bytree': 0.5393776820447042, 'reg_alpha': 6.061029273544998e-05, 'reg_lambda': 0.0020237631280064475}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:47,010] Trial 85 finished with value: 0.9716479173000911 and parameters: {'n_estimators': 648, 'max_depth': 3, 'learning_rate': 0.25369031622209937, 'gamma': 0.011189099120964408, 'min_child_weight': 1, 'subsample': 0.9618607275528647, 'colsample_bytree': 0.5403278959911854, 'reg_alpha': 6.770838783028626e-05, 'reg_lambda': 0.004437258057055608}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:47,109] Trial 86 finished with value: 0.969990878686531 and parameters: {'n_estimators': 765, 'max_depth': 2, 'learning_rate': 0.24109962829948212, 'gamma': 0.010123695604080735, 'min_child_weight': 1, 'subsample': 0.9745058224401574, 'colsample_bytree': 0.5299920014608653, 'reg_alpha': 3.632267987330727e-05, 'reg_lambda': 0.009842578847590693}. Best is trial 77 with value: 0.9755472788081484.\n", + "[I 2025-08-18 23:04:47,206] Trial 87 finished with value: 0.9775793047532177 and parameters: {'n_estimators': 636, 'max_depth': 3, 'learning_rate': 0.28911459468011935, 'gamma': 0.0026877179567177173, 'min_child_weight': 1, 'subsample': 0.9884898945689472, 'colsample_bytree': 0.5529899112143574, 'reg_alpha': 8.780578569353003e-06, 'reg_lambda': 0.024175358439225716}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,291] Trial 88 finished with value: 0.9618374379243946 and parameters: {'n_estimators': 630, 'max_depth': 3, 'learning_rate': 0.3030644325616155, 'gamma': 0.0014905115676082498, 'min_child_weight': 7, 'subsample': 0.9611256405654685, 'colsample_bytree': 0.5008769080768224, 'reg_alpha': 8.389249095912817e-07, 'reg_lambda': 0.025573250031303514}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,384] Trial 89 finished with value: 0.9702391811087464 and parameters: {'n_estimators': 648, 'max_depth': 2, 'learning_rate': 0.24974925657004052, 'gamma': 0.005400230740828263, 'min_child_weight': 2, 'subsample': 0.98727769647163, 'colsample_bytree': 0.542979554752891, 'reg_alpha': 6.773579449524946e-05, 'reg_lambda': 0.13938797071958295}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,484] Trial 90 finished with value: 0.9713134691395562 and parameters: {'n_estimators': 678, 'max_depth': 4, 'learning_rate': 0.27329622005890974, 'gamma': 0.0025640663065522483, 'min_child_weight': 1, 'subsample': 0.9685762941440739, 'colsample_bytree': 0.5533183680424663, 'reg_alpha': 9.554742944191967e-06, 'reg_lambda': 0.05646506170705333}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,600] Trial 91 finished with value: 0.9720735785953177 and parameters: {'n_estimators': 685, 'max_depth': 4, 'learning_rate': 0.27964910528085046, 'gamma': 0.002726438477417822, 'min_child_weight': 1, 'subsample': 0.9999643990452035, 'colsample_bytree': 0.5523292566223091, 'reg_alpha': 1.3960839467745119e-05, 'reg_lambda': 0.01415347048036145}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,692] Trial 92 finished with value: 0.9752204317421709 and parameters: {'n_estimators': 593, 'max_depth': 4, 'learning_rate': 0.32272873880627245, 'gamma': 0.0003076681496953475, 'min_child_weight': 1, 'subsample': 0.9988143324319202, 'colsample_bytree': 0.5182298233134042, 'reg_alpha': 4.764947763017983e-06, 'reg_lambda': 0.012883267517371262}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,777] Trial 93 finished with value: 0.9702746528833485 and parameters: {'n_estimators': 592, 'max_depth': 4, 'learning_rate': 0.32321683238270205, 'gamma': 0.00023242624645060717, 'min_child_weight': 1, 'subsample': 0.9883656895313044, 'colsample_bytree': 0.5249002470585026, 'reg_alpha': 3.177832241884098e-06, 'reg_lambda': 0.017907514716424745}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,866] Trial 94 finished with value: 0.9754687341643864 and parameters: {'n_estimators': 719, 'max_depth': 5, 'learning_rate': 0.35309665196705153, 'gamma': 0.0012381542386533933, 'min_child_weight': 2, 'subsample': 0.9938001959815986, 'colsample_bytree': 0.5135263406023138, 'reg_alpha': 2.140299584024884e-05, 'reg_lambda': 0.010354897273928652}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:47,964] Trial 95 finished with value: 0.9702619843924193 and parameters: {'n_estimators': 813, 'max_depth': 4, 'learning_rate': 0.35202078039521256, 'gamma': 0.0008558118176606106, 'min_child_weight': 2, 'subsample': 0.9786791914929385, 'colsample_bytree': 0.5169883732201127, 'reg_alpha': 4.819331670670429e-06, 'reg_lambda': 0.01225335075642242}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,050] Trial 96 finished with value: 0.9659420289855072 and parameters: {'n_estimators': 549, 'max_depth': 5, 'learning_rate': 0.30573045471770227, 'gamma': 0.0006382196831107483, 'min_child_weight': 2, 'subsample': 0.9975854577557746, 'colsample_bytree': 0.5149033410261374, 'reg_alpha': 1.7285610267319068e-05, 'reg_lambda': 0.04954756540940724}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,140] Trial 97 finished with value: 0.9701733049559136 and parameters: {'n_estimators': 726, 'max_depth': 2, 'learning_rate': 0.2877388004810307, 'gamma': 0.0003280781904783974, 'min_child_weight': 1, 'subsample': 0.9563657324404314, 'colsample_bytree': 0.5071027752196428, 'reg_alpha': 1.6962797991959727e-05, 'reg_lambda': 0.00907410879093517}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,228] Trial 98 finished with value: 0.9579279416235937 and parameters: {'n_estimators': 753, 'max_depth': 1, 'learning_rate': 0.34676644343134116, 'gamma': 0.0012565205080685606, 'min_child_weight': 2, 'subsample': 0.9724664289612212, 'colsample_bytree': 0.5608401123520345, 'reg_alpha': 1.398799276624877e-06, 'reg_lambda': 0.15340330599489194}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,317] Trial 99 finished with value: 0.9712729299685823 and parameters: {'n_estimators': 628, 'max_depth': 3, 'learning_rate': 0.3685623760852724, 'gamma': 0.00016314010705137475, 'min_child_weight': 1, 'subsample': 0.9018849176689584, 'colsample_bytree': 0.5526193503254366, 'reg_alpha': 3.4172598118958266e-06, 'reg_lambda': 0.35726720012149144}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,408] Trial 100 finished with value: 0.9684123847167324 and parameters: {'n_estimators': 685, 'max_depth': 5, 'learning_rate': 0.32205265663271354, 'gamma': 0.0003733394372953507, 'min_child_weight': 2, 'subsample': 0.9269329238786695, 'colsample_bytree': 0.5328390047076582, 'reg_alpha': 6.468453572696246e-06, 'reg_lambda': 0.0247247964033616}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,492] Trial 101 finished with value: 0.9734341745211312 and parameters: {'n_estimators': 657, 'max_depth': 4, 'learning_rate': 0.2902610534781817, 'gamma': 0.003144326892729591, 'min_child_weight': 1, 'subsample': 0.9994520720533928, 'colsample_bytree': 0.5979372134689044, 'reg_alpha': 2.811792565093441e-05, 'reg_lambda': 0.0024288390385784997}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,590] Trial 102 finished with value: 0.9678017634539373 and parameters: {'n_estimators': 794, 'max_depth': 4, 'learning_rate': 0.29965776922838716, 'gamma': 0.003105619445624373, 'min_child_weight': 1, 'subsample': 0.9811178081384474, 'colsample_bytree': 0.5970710263821791, 'reg_alpha': 3.448408606278336e-05, 'reg_lambda': 0.0025213111005363957}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,680] Trial 103 finished with value: 0.9684681260768218 and parameters: {'n_estimators': 663, 'max_depth': 4, 'learning_rate': 0.26839935650628705, 'gamma': 0.0005156188710353528, 'min_child_weight': 1, 'subsample': 0.9892553837421945, 'colsample_bytree': 0.5402218509766766, 'reg_alpha': 1.2238097567923076e-05, 'reg_lambda': 0.013305019890137302}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,768] Trial 104 finished with value: 0.9755194081281037 and parameters: {'n_estimators': 560, 'max_depth': 3, 'learning_rate': 0.28236255406126465, 'gamma': 0.004741677790575585, 'min_child_weight': 1, 'subsample': 0.9531167819448579, 'colsample_bytree': 0.5099770858154159, 'reg_alpha': 2.984910631985938e-05, 'reg_lambda': 0.007518398425430544}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,857] Trial 105 finished with value: 0.9730085132259045 and parameters: {'n_estimators': 596, 'max_depth': 2, 'learning_rate': 0.3222004116025429, 'gamma': 0.004489752812161376, 'min_child_weight': 1, 'subsample': 0.9352956487444385, 'colsample_bytree': 0.5865015029021471, 'reg_alpha': 2.7008940823248416e-05, 'reg_lambda': 0.007828445330780436}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:48,937] Trial 106 finished with value: 0.9669631093544137 and parameters: {'n_estimators': 595, 'max_depth': 2, 'learning_rate': 0.3267714012542968, 'gamma': 0.0016705946716529846, 'min_child_weight': 1, 'subsample': 0.9536853948914599, 'colsample_bytree': 0.5893227042142406, 'reg_alpha': 2.1190401208330304e-05, 'reg_lambda': 0.0063492970335785335}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,012] Trial 107 finished with value: 0.9649944258639911 and parameters: {'n_estimators': 551, 'max_depth': 1, 'learning_rate': 0.3576194826916017, 'gamma': 0.004801886110733527, 'min_child_weight': 6, 'subsample': 0.9338819770386118, 'colsample_bytree': 0.6214947240444341, 'reg_alpha': 2.8234266675465392e-05, 'reg_lambda': 0.008051822527829319}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,099] Trial 108 finished with value: 0.9720609101043882 and parameters: {'n_estimators': 595, 'max_depth': 3, 'learning_rate': 0.31458876017437437, 'gamma': 0.008358899230048938, 'min_child_weight': 1, 'subsample': 0.968750010105244, 'colsample_bytree': 0.6043042278252939, 'reg_alpha': 2.393229312399412e-06, 'reg_lambda': 0.0021086902788013838}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,176] Trial 109 finished with value: 0.9595520421607379 and parameters: {'n_estimators': 564, 'max_depth': 3, 'learning_rate': 0.29332591763899823, 'gamma': 0.002008519656446403, 'min_child_weight': 10, 'subsample': 0.9178749512403971, 'colsample_bytree': 0.5624548512353742, 'reg_alpha': 6.279674953618662e-05, 'reg_lambda': 0.03769905974473238}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,256] Trial 110 finished with value: 0.9681640822945171 and parameters: {'n_estimators': 627, 'max_depth': 2, 'learning_rate': 0.21619927350223261, 'gamma': 0.0009373960888666258, 'min_child_weight': 2, 'subsample': 0.6307794924226682, 'colsample_bytree': 0.5836006154710169, 'reg_alpha': 2.713808381396758e-07, 'reg_lambda': 0.0050776218812680785}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,342] Trial 111 finished with value: 0.9708346001824262 and parameters: {'n_estimators': 651, 'max_depth': 5, 'learning_rate': 0.40366773427286373, 'gamma': 0.005707361249345923, 'min_child_weight': 1, 'subsample': 0.9799469111616341, 'colsample_bytree': 0.5116600324384395, 'reg_alpha': 8.85253713948703e-06, 'reg_lambda': 0.003065231130945774}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,432] Trial 112 finished with value: 0.9736951454342758 and parameters: {'n_estimators': 583, 'max_depth': 3, 'learning_rate': 0.37574148917155586, 'gamma': 0.0009319568992135199, 'min_child_weight': 1, 'subsample': 0.9397410388904857, 'colsample_bytree': 0.5235594910355523, 'reg_alpha': 4.017162866775182e-05, 'reg_lambda': 0.018251272759087948}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,520] Trial 113 finished with value: 0.973771156379852 and parameters: {'n_estimators': 578, 'max_depth': 3, 'learning_rate': 0.380812899535783, 'gamma': 0.0011512223457226971, 'min_child_weight': 1, 'subsample': 0.9388546288873797, 'colsample_bytree': 0.5352536425774438, 'reg_alpha': 9.09130166376462e-05, 'reg_lambda': 0.018725988923139904}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,598] Trial 114 finished with value: 0.9737838248707813 and parameters: {'n_estimators': 530, 'max_depth': 3, 'learning_rate': 0.3742761757944042, 'gamma': 0.0029273154938769808, 'min_child_weight': 1, 'subsample': 0.9529626320951139, 'colsample_bytree': 0.5232564805201162, 'reg_alpha': 9.104169023548576e-05, 'reg_lambda': 0.01996768613708404}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,681] Trial 115 finished with value: 0.9756460930373974 and parameters: {'n_estimators': 533, 'max_depth': 3, 'learning_rate': 0.3787657790858809, 'gamma': 0.0011307839139740017, 'min_child_weight': 1, 'subsample': 0.9535686443026108, 'colsample_bytree': 0.5245456491257551, 'reg_alpha': 0.00013522790859490737, 'reg_lambda': 0.019711799698721878}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,755] Trial 116 finished with value: 0.9635198135198134 and parameters: {'n_estimators': 485, 'max_depth': 3, 'learning_rate': 0.38091477840580124, 'gamma': 0.0009720468741725009, 'min_child_weight': 2, 'subsample': 0.8986807103789741, 'colsample_bytree': 0.5273155593064995, 'reg_alpha': 0.00013848719337144623, 'reg_lambda': 0.08091061668198583}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,834] Trial 117 finished with value: 0.9717289956420393 and parameters: {'n_estimators': 527, 'max_depth': 4, 'learning_rate': 0.4076052802456525, 'gamma': 0.0004831402272338826, 'min_child_weight': 1, 'subsample': 0.9533851366158632, 'colsample_bytree': 0.5220037354837226, 'reg_alpha': 4.5139430500113255e-05, 'reg_lambda': 0.02575574317660115}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:49,924] Trial 118 finished with value: 0.9752331002331003 and parameters: {'n_estimators': 563, 'max_depth': 3, 'learning_rate': 0.369521549644023, 'gamma': 0.0033558215982748703, 'min_child_weight': 1, 'subsample': 0.9667985061852574, 'colsample_bytree': 0.5372400830436947, 'reg_alpha': 9.504911886451962e-05, 'reg_lambda': 0.018904666487589226}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,013] Trial 119 finished with value: 0.9705736292692814 and parameters: {'n_estimators': 563, 'max_depth': 4, 'learning_rate': 0.4299915817303335, 'gamma': 0.001525288316607799, 'min_child_weight': 1, 'subsample': 0.9689561356982478, 'colsample_bytree': 0.5359613906712454, 'reg_alpha': 8.351303475967823e-05, 'reg_lambda': 0.018419935953742344}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,090] Trial 120 finished with value: 0.9639074693422518 and parameters: {'n_estimators': 451, 'max_depth': 3, 'learning_rate': 0.3667210874551086, 'gamma': 0.0021214031984273544, 'min_child_weight': 2, 'subsample': 0.9432651878904321, 'colsample_bytree': 0.5014124944408871, 'reg_alpha': 0.0003167811707490163, 'reg_lambda': 0.04607793156075455}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,171] Trial 121 finished with value: 0.9724004256612953 and parameters: {'n_estimators': 580, 'max_depth': 3, 'learning_rate': 0.38856872366310524, 'gamma': 0.0007746428169296834, 'min_child_weight': 1, 'subsample': 0.9623910956260555, 'colsample_bytree': 0.5119448445892998, 'reg_alpha': 0.0001022046692298684, 'reg_lambda': 0.01876632074345833}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,249] Trial 122 finished with value: 0.9663018141279013 and parameters: {'n_estimators': 523, 'max_depth': 5, 'learning_rate': 0.34228646898366927, 'gamma': 0.004028194445590085, 'min_child_weight': 1, 'subsample': 0.9828478575776481, 'colsample_bytree': 0.5450122834491693, 'reg_alpha': 4.336905329638909e-05, 'reg_lambda': 0.07311566300587641}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,326] Trial 123 finished with value: 0.9660028377419682 and parameters: {'n_estimators': 543, 'max_depth': 2, 'learning_rate': 0.3710652116662308, 'gamma': 0.003426110492596931, 'min_child_weight': 1, 'subsample': 0.9519074894178458, 'colsample_bytree': 0.52062981297652, 'reg_alpha': 0.00019606561378930507, 'reg_lambda': 0.00010956050738603163}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,402] Trial 124 finished with value: 0.9675078544643763 and parameters: {'n_estimators': 490, 'max_depth': 3, 'learning_rate': 0.3419021639421203, 'gamma': 0.001379753702423482, 'min_child_weight': 1, 'subsample': 0.5402074886692497, 'colsample_bytree': 0.534963564474138, 'reg_alpha': 2.4804707361280354e-05, 'reg_lambda': 0.02366181477486779}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,492] Trial 125 finished with value: 0.9664031620553359 and parameters: {'n_estimators': 623, 'max_depth': 4, 'learning_rate': 0.2584426107557688, 'gamma': 0.0002969583549970284, 'min_child_weight': 1, 'subsample': 0.8659075091283825, 'colsample_bytree': 0.5477391905798454, 'reg_alpha': 6.0849397689869715e-06, 'reg_lambda': 0.03055499300789043}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,569] Trial 126 finished with value: 0.9709739535826492 and parameters: {'n_estimators': 564, 'max_depth': 3, 'learning_rate': 0.3607708090917786, 'gamma': 0.007904872146312887, 'min_child_weight': 1, 'subsample': 0.9732660624180509, 'colsample_bytree': 0.5596402152998722, 'reg_alpha': 0.0001532572414280914, 'reg_lambda': 0.1245305580605709}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,660] Trial 127 finished with value: 0.9620680044593088 and parameters: {'n_estimators': 507, 'max_depth': 6, 'learning_rate': 0.40969970909179665, 'gamma': 0.002569636211762046, 'min_child_weight': 2, 'subsample': 0.8829928862860841, 'colsample_bytree': 0.5098754820895927, 'reg_alpha': 1.3035647256514827e-05, 'reg_lambda': 0.010289122123771933}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,736] Trial 128 finished with value: 0.9603476233911017 and parameters: {'n_estimators': 577, 'max_depth': 1, 'learning_rate': 0.39060663548307156, 'gamma': 0.0010891361828261408, 'min_child_weight': 1, 'subsample': 0.9379188131627437, 'colsample_bytree': 0.524948913298735, 'reg_alpha': 8.586777823699555e-05, 'reg_lambda': 0.04302715195504146}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,817] Trial 129 finished with value: 0.9663702239789196 and parameters: {'n_estimators': 546, 'max_depth': 2, 'learning_rate': 0.3340394526859328, 'gamma': 0.005928493392740887, 'min_child_weight': 1, 'subsample': 0.9854164381951216, 'colsample_bytree': 0.5401827154061658, 'reg_alpha': 3.574390952002835e-05, 'reg_lambda': 0.01684875458666302}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,905] Trial 130 finished with value: 0.9653162055335969 and parameters: {'n_estimators': 616, 'max_depth': 4, 'learning_rate': 0.28549506379050643, 'gamma': 1.2263018757725954e-07, 'min_child_weight': 2, 'subsample': 0.959035504220871, 'colsample_bytree': 0.5004808635645343, 'reg_alpha': 6.108068069373782e-05, 'reg_lambda': 4.081789431923016e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:50,995] Trial 131 finished with value: 0.974407114624506 and parameters: {'n_estimators': 607, 'max_depth': 5, 'learning_rate': 0.355606899809378, 'gamma': 0.0016875775407594427, 'min_child_weight': 1, 'subsample': 0.9899274318285423, 'colsample_bytree': 0.522467631554332, 'reg_alpha': 1.9439920919411324e-05, 'reg_lambda': 0.005478042686972311}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,083] Trial 132 finished with value: 0.9697349751697578 and parameters: {'n_estimators': 659, 'max_depth': 5, 'learning_rate': 0.3758099733710491, 'gamma': 0.0020911550697864313, 'min_child_weight': 1, 'subsample': 0.9896734709877024, 'colsample_bytree': 0.5200962421716877, 'reg_alpha': 1.0531070308464693e-05, 'reg_lambda': 0.006260553029093111}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,160] Trial 133 finished with value: 0.9691623593797507 and parameters: {'n_estimators': 579, 'max_depth': 4, 'learning_rate': 0.3543435466787781, 'gamma': 0.003457287339258925, 'min_child_weight': 1, 'subsample': 0.9699357364188769, 'colsample_bytree': 0.5319377512135547, 'reg_alpha': 1.6344689723836534e-05, 'reg_lambda': 0.011513426714595142}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,249] Trial 134 finished with value: 0.9685137326441675 and parameters: {'n_estimators': 609, 'max_depth': 3, 'learning_rate': 0.29969094509558114, 'gamma': 0.0006201750540023973, 'min_child_weight': 1, 'subsample': 0.9465508766827356, 'colsample_bytree': 0.549628779727799, 'reg_alpha': 0.00023383467565098683, 'reg_lambda': 0.00473897887352641}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,340] Trial 135 finished with value: 0.9702113104287017 and parameters: {'n_estimators': 702, 'max_depth': 5, 'learning_rate': 0.39838626436610647, 'gamma': 0.013457480792657921, 'min_child_weight': 1, 'subsample': 0.9284918315242744, 'colsample_bytree': 0.5111760740688991, 'reg_alpha': 2.112013867824408e-05, 'reg_lambda': 0.0016412145138216558}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,416] Trial 136 finished with value: 0.9590706395054222 and parameters: {'n_estimators': 423, 'max_depth': 3, 'learning_rate': 0.42953000397831703, 'gamma': 0.0017375341373862645, 'min_child_weight': 9, 'subsample': 0.9781959850635785, 'colsample_bytree': 0.8378674178811536, 'reg_alpha': 9.858181986503538e-05, 'reg_lambda': 0.0322880013964512}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,504] Trial 137 finished with value: 0.973811695550826 and parameters: {'n_estimators': 728, 'max_depth': 4, 'learning_rate': 0.3342825551208779, 'gamma': 0.0013440099679389622, 'min_child_weight': 1, 'subsample': 0.9916941709687607, 'colsample_bytree': 0.5655061047088268, 'reg_alpha': 5.070174259490981e-05, 'reg_lambda': 0.05985267611255229}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,604] Trial 138 finished with value: 0.9692383703253269 and parameters: {'n_estimators': 749, 'max_depth': 4, 'learning_rate': 0.32844184046054403, 'gamma': 0.0010007539710985736, 'min_child_weight': 5, 'subsample': 0.9920762896755643, 'colsample_bytree': 0.565157003127687, 'reg_alpha': 4.908631252458206e-05, 'reg_lambda': 0.0959049021065359}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,694] Trial 139 finished with value: 0.9708852741461437 and parameters: {'n_estimators': 673, 'max_depth': 5, 'learning_rate': 0.3774025399941191, 'gamma': 0.000643044874536142, 'min_child_weight': 1, 'subsample': 0.9651415410028824, 'colsample_bytree': 0.5256854732827111, 'reg_alpha': 4.714024807154563e-06, 'reg_lambda': 0.9912937619442326}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,783] Trial 140 finished with value: 0.9634792743488395 and parameters: {'n_estimators': 717, 'max_depth': 2, 'learning_rate': 0.3137203687154433, 'gamma': 0.0003873298406166423, 'min_child_weight': 1, 'subsample': 0.9913943483341556, 'colsample_bytree': 0.5377420413971642, 'reg_alpha': 3.32220834872906e-05, 'reg_lambda': 0.056686545270045595}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,872] Trial 141 finished with value: 0.9681032735380561 and parameters: {'n_estimators': 732, 'max_depth': 4, 'learning_rate': 0.3457977422562131, 'gamma': 0.002976971721662494, 'min_child_weight': 1, 'subsample': 0.9763124432392175, 'colsample_bytree': 0.5543880729679166, 'reg_alpha': 7.545227219322496e-05, 'reg_lambda': 0.009449314626667723}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:51,962] Trial 142 finished with value: 0.9723598864903213 and parameters: {'n_estimators': 632, 'max_depth': 3, 'learning_rate': 0.275963901659525, 'gamma': 0.0016243745622636782, 'min_child_weight': 1, 'subsample': 0.9530092292388275, 'colsample_bytree': 0.5175852195916012, 'reg_alpha': 0.0001427649603465201, 'reg_lambda': 0.0005683368270736766}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,051] Trial 143 finished with value: 0.9677688253775212 and parameters: {'n_estimators': 592, 'max_depth': 6, 'learning_rate': 0.3336579888058368, 'gamma': 0.00014631390669258675, 'min_child_weight': 1, 'subsample': 0.9999417063182031, 'colsample_bytree': 0.9335216594524222, 'reg_alpha': 4.6191952330179104e-05, 'reg_lambda': 0.016752760821593927}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,141] Trial 144 finished with value: 0.9641684402553968 and parameters: {'n_estimators': 529, 'max_depth': 4, 'learning_rate': 0.36114155417739013, 'gamma': 0.0013312075417919174, 'min_child_weight': 1, 'subsample': 0.9623533998092761, 'colsample_bytree': 0.5302807739145121, 'reg_alpha': 1.9198762008560404e-06, 'reg_lambda': 0.02423055657998778}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,232] Trial 145 finished with value: 0.9663144826188306 and parameters: {'n_estimators': 696, 'max_depth': 3, 'learning_rate': 0.29694209248501263, 'gamma': 0.006637136428949488, 'min_child_weight': 2, 'subsample': 0.9832551742092744, 'colsample_bytree': 0.5451968446750411, 'reg_alpha': 2.3355865575390215e-05, 'reg_lambda': 6.480226641591573e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,323] Trial 146 finished with value: 0.9722458700719571 and parameters: {'n_estimators': 772, 'max_depth': 2, 'learning_rate': 0.3119949296748683, 'gamma': 0.004385003172565624, 'min_child_weight': 1, 'subsample': 0.911161698166705, 'colsample_bytree': 0.5674565521458058, 'reg_alpha': 8.339882112703323e-06, 'reg_lambda': 0.22744493185559642}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,414] Trial 147 finished with value: 0.9705989662511403 and parameters: {'n_estimators': 649, 'max_depth': 5, 'learning_rate': 0.3886513667571667, 'gamma': 0.0023992741913581236, 'min_child_weight': 1, 'subsample': 0.9412909731446526, 'colsample_bytree': 0.5082665367483681, 'reg_alpha': 1.3917011685173996e-05, 'reg_lambda': 0.004983404179282378}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,505] Trial 148 finished with value: 0.9641785750481404 and parameters: {'n_estimators': 559, 'max_depth': 7, 'learning_rate': 0.2656435390958021, 'gamma': 0.010482805664855063, 'min_child_weight': 1, 'subsample': 0.9700690013382033, 'colsample_bytree': 0.553896550744323, 'reg_alpha': 2.703827604890988e-05, 'reg_lambda': 0.008979484259118622}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,595] Trial 149 finished with value: 0.9656785243741766 and parameters: {'n_estimators': 675, 'max_depth': 4, 'learning_rate': 0.3481169895361487, 'gamma': 0.0190297439645008, 'min_child_weight': 1, 'subsample': 0.9886286410235502, 'colsample_bytree': 0.5248371166735615, 'reg_alpha': 0.00011080258805194705, 'reg_lambda': 0.013823520690237876}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,686] Trial 150 finished with value: 0.971652984696463 and parameters: {'n_estimators': 610, 'max_depth': 3, 'learning_rate': 0.3647380803471352, 'gamma': 0.0007750215340674814, 'min_child_weight': 2, 'subsample': 0.9544048764946547, 'colsample_bytree': 0.578212060417031, 'reg_alpha': 0.0003801255473377791, 'reg_lambda': 0.03725850213457456}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,776] Trial 151 finished with value: 0.9720229046316003 and parameters: {'n_estimators': 592, 'max_depth': 9, 'learning_rate': 0.3464425517062153, 'gamma': 0.0012319969445261018, 'min_child_weight': 1, 'subsample': 0.9985073180656334, 'colsample_bytree': 0.5974960617683841, 'reg_alpha': 5.515700111193299e-05, 'reg_lambda': 0.0033159882823894545}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,865] Trial 152 finished with value: 0.9688507145028884 and parameters: {'n_estimators': 540, 'max_depth': 4, 'learning_rate': 0.38017768085764003, 'gamma': 0.002973199513913439, 'min_child_weight': 1, 'subsample': 0.9799912178341434, 'colsample_bytree': 0.5404784885391826, 'reg_alpha': 3.899089387434627e-05, 'reg_lambda': 0.0015310715824011964}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:52,954] Trial 153 finished with value: 0.9699376710246275 and parameters: {'n_estimators': 638, 'max_depth': 3, 'learning_rate': 0.3293247587583182, 'gamma': 1.080918771118752e-08, 'min_child_weight': 1, 'subsample': 0.9748569594260413, 'colsample_bytree': 0.5627494059605304, 'reg_alpha': 0.0001868642563379178, 'reg_lambda': 0.00610063335717874}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,045] Trial 154 finished with value: 0.9727247390290866 and parameters: {'n_estimators': 579, 'max_depth': 8, 'learning_rate': 0.3590865853470216, 'gamma': 0.00023242766577177755, 'min_child_weight': 1, 'subsample': 0.9961763419959316, 'colsample_bytree': 0.5001855233864979, 'reg_alpha': 4.938473306881137e-06, 'reg_lambda': 0.05945419728506628}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,132] Trial 155 finished with value: 0.9698236546062633 and parameters: {'n_estimators': 511, 'max_depth': 2, 'learning_rate': 0.23177088731265877, 'gamma': 0.00220051619789768, 'min_child_weight': 1, 'subsample': 0.9617219946146195, 'colsample_bytree': 0.5155296562213243, 'reg_alpha': 0.41356358892481515, 'reg_lambda': 0.0021647051888757846}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,221] Trial 156 finished with value: 0.9642849903719469 and parameters: {'n_estimators': 608, 'max_depth': 4, 'learning_rate': 0.310179089365562, 'gamma': 0.0004899069210826855, 'min_child_weight': 1, 'subsample': 0.989151895567528, 'colsample_bytree': 0.6155162461276559, 'reg_alpha': 7.038828394482472e-05, 'reg_lambda': 0.018486913379264905}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,306] Trial 157 finished with value: 0.968800040539171 and parameters: {'n_estimators': 625, 'max_depth': 3, 'learning_rate': 0.28337124920511253, 'gamma': 0.005312986290264966, 'min_child_weight': 1, 'subsample': 0.9471200013006852, 'colsample_bytree': 0.5371368095603188, 'reg_alpha': 2.126502030369528e-05, 'reg_lambda': 0.007672507188909957}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,396] Trial 158 finished with value: 0.9688127090301004 and parameters: {'n_estimators': 560, 'max_depth': 5, 'learning_rate': 0.24864922427836095, 'gamma': 0.001724231530528261, 'min_child_weight': 1, 'subsample': 0.9275859919551936, 'colsample_bytree': 0.5485555398820796, 'reg_alpha': 0.22167735775120456, 'reg_lambda': 0.012725979226750948}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,472] Trial 159 finished with value: 0.9690990169251039 and parameters: {'n_estimators': 466, 'max_depth': 7, 'learning_rate': 0.4138830978222457, 'gamma': 0.008325545281432306, 'min_child_weight': 2, 'subsample': 0.9825726014682536, 'colsample_bytree': 0.5288970024992221, 'reg_alpha': 1.1950616323811105e-05, 'reg_lambda': 0.004148040954584921}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,575] Trial 160 finished with value: 0.9681007398398702 and parameters: {'n_estimators': 665, 'max_depth': 2, 'learning_rate': 0.10656692051303243, 'gamma': 0.0034721265000381826, 'min_child_weight': 1, 'subsample': 0.6041603502459372, 'colsample_bytree': 0.8973681381628347, 'reg_alpha': 8.155092256320305e-07, 'reg_lambda': 0.0026912192428167675}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,653] Trial 161 finished with value: 0.9741334752204317 and parameters: {'n_estimators': 593, 'max_depth': 2, 'learning_rate': 0.3316977172429725, 'gamma': 0.00442101924584059, 'min_child_weight': 1, 'subsample': 0.9383014449372667, 'colsample_bytree': 0.583117916065411, 'reg_alpha': 3.380931076086002e-05, 'reg_lambda': 0.008524632802382586}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,731] Trial 162 finished with value: 0.9709106111280026 and parameters: {'n_estimators': 592, 'max_depth': 3, 'learning_rate': 0.3361791828373549, 'gamma': 0.000985104918156739, 'min_child_weight': 1, 'subsample': 0.9689753750776854, 'colsample_bytree': 0.582026572904053, 'reg_alpha': 2.9623097239471037e-05, 'reg_lambda': 0.023865897227663392}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,818] Trial 163 finished with value: 0.972364953886693 and parameters: {'n_estimators': 544, 'max_depth': 2, 'learning_rate': 0.36753628914761743, 'gamma': 0.003867620019904887, 'min_child_weight': 1, 'subsample': 0.9163941822885812, 'colsample_bytree': 0.5934172796052541, 'reg_alpha': 1.6872233434997325e-05, 'reg_lambda': 0.0012256804410906703}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,909] Trial 164 finished with value: 0.9649538866930174 and parameters: {'n_estimators': 644, 'max_depth': 4, 'learning_rate': 0.3217185820552294, 'gamma': 0.9074683779076849, 'min_child_weight': 1, 'subsample': 0.9404194835151828, 'colsample_bytree': 0.5716382974503587, 'reg_alpha': 4.5156868287806393e-05, 'reg_lambda': 0.009577284570238343}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:53,989] Trial 165 finished with value: 0.9582623897841289 and parameters: {'n_estimators': 572, 'max_depth': 1, 'learning_rate': 0.35434018519246835, 'gamma': 0.006054890244988751, 'min_child_weight': 1, 'subsample': 0.9565629468808314, 'colsample_bytree': 0.6064348733438767, 'reg_alpha': 0.00011506343284625452, 'reg_lambda': 0.03650487541601268}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,068] Trial 166 finished with value: 0.9660433769129421 and parameters: {'n_estimators': 606, 'max_depth': 3, 'learning_rate': 0.2967811217926221, 'gamma': 0.002177647575750638, 'min_child_weight': 4, 'subsample': 0.998649545486057, 'colsample_bytree': 0.5185902261954761, 'reg_alpha': 8.042129768295383e-05, 'reg_lambda': 0.014443731544619897}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,147] Trial 167 finished with value: 0.9681007398398702 and parameters: {'n_estimators': 690, 'max_depth': 4, 'learning_rate': 0.38997942152940307, 'gamma': 0.0013930912234913896, 'min_child_weight': 1, 'subsample': 0.977585735981025, 'colsample_bytree': 0.5600326728904678, 'reg_alpha': 8.024671426853231e-06, 'reg_lambda': 0.005881071752141783}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,225] Trial 168 finished with value: 0.9663524880916186 and parameters: {'n_estimators': 518, 'max_depth': 9, 'learning_rate': 0.37517946961696524, 'gamma': 0.2884197766559136, 'min_child_weight': 2, 'subsample': 0.9320238547852112, 'colsample_bytree': 0.5116644916138443, 'reg_alpha': 3.510454301920386e-05, 'reg_lambda': 0.00396091516537362}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,303] Trial 169 finished with value: 0.9733835005574136 and parameters: {'n_estimators': 493, 'max_depth': 3, 'learning_rate': 0.323016657794504, 'gamma': 0.0008040858558472051, 'min_child_weight': 1, 'subsample': 0.9650583288653142, 'colsample_bytree': 0.5335385167426343, 'reg_alpha': 0.00025883717994882905, 'reg_lambda': 1.4790057261225227e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,397] Trial 170 finished with value: 0.9701986419377724 and parameters: {'n_estimators': 490, 'max_depth': 3, 'learning_rate': 0.321492205338363, 'gamma': 0.0007229956299063446, 'min_child_weight': 1, 'subsample': 0.9471452120455542, 'colsample_bytree': 0.5341908031859132, 'reg_alpha': 5.7889158157425586e-05, 'reg_lambda': 2.5464473413471723e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,464] Trial 171 finished with value: 0.9694106618019662 and parameters: {'n_estimators': 215, 'max_depth': 2, 'learning_rate': 0.3439161658472922, 'gamma': 0.0011441221668909544, 'min_child_weight': 1, 'subsample': 0.9634326817470634, 'colsample_bytree': 0.5247209277418037, 'reg_alpha': 0.00016940381362453118, 'reg_lambda': 0.02385174376916467}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,555] Trial 172 finished with value: 0.9706167021384413 and parameters: {'n_estimators': 619, 'max_depth': 3, 'learning_rate': 0.3054421107140958, 'gamma': 0.0026032231277366247, 'min_child_weight': 1, 'subsample': 0.9860629143288514, 'colsample_bytree': 0.547967448961253, 'reg_alpha': 0.0002849202968485869, 'reg_lambda': 2.6299709321578504e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,645] Trial 173 finished with value: 0.971946893686024 and parameters: {'n_estimators': 720, 'max_depth': 4, 'learning_rate': 0.33341255577347795, 'gamma': 0.0016105012826958308, 'min_child_weight': 1, 'subsample': 0.9679139315267277, 'colsample_bytree': 0.5386463925647356, 'reg_alpha': 8.43176289243587e-05, 'reg_lambda': 4.340287507851219e-06}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,724] Trial 174 finished with value: 0.9716605857910207 and parameters: {'n_estimators': 557, 'max_depth': 5, 'learning_rate': 0.2901160057271195, 'gamma': 0.00032942746566321543, 'min_child_weight': 1, 'subsample': 0.9765070332415594, 'colsample_bytree': 0.5071537214617675, 'reg_alpha': 0.0004723169262131176, 'reg_lambda': 6.832514561560678e-06}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,805] Trial 175 finished with value: 0.9691116854160333 and parameters: {'n_estimators': 588, 'max_depth': 3, 'learning_rate': 0.3522900041666762, 'gamma': 0.004165093913741628, 'min_child_weight': 1, 'subsample': 0.9999358736000473, 'colsample_bytree': 0.5570975897786812, 'reg_alpha': 0.00011310018708618362, 'reg_lambda': 1.5899845363994675e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,907] Trial 176 finished with value: 0.9701859734468432 and parameters: {'n_estimators': 795, 'max_depth': 3, 'learning_rate': 0.2661263579232849, 'gamma': 0.0005314614635974421, 'min_child_weight': 1, 'subsample': 0.955262002780409, 'colsample_bytree': 0.5218601743864764, 'reg_alpha': 3.278095954186388e-05, 'reg_lambda': 0.007563842393120928}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:54,987] Trial 177 finished with value: 0.9691876963616094 and parameters: {'n_estimators': 528, 'max_depth': 4, 'learning_rate': 0.4052836482941531, 'gamma': 0.0007836995912045476, 'min_child_weight': 1, 'subsample': 0.9835358139883751, 'colsample_bytree': 0.5748069554328435, 'reg_alpha': 1.8927713418645845e-05, 'reg_lambda': 0.016993878052280156}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,078] Trial 178 finished with value: 0.9646042363433669 and parameters: {'n_estimators': 659, 'max_depth': 10, 'learning_rate': 0.3716414273907836, 'gamma': 0.0030133506411139394, 'min_child_weight': 2, 'subsample': 0.9398036029857711, 'colsample_bytree': 0.53143727573368, 'reg_alpha': 0.00023311010825420792, 'reg_lambda': 0.012640641270748694}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,167] Trial 179 finished with value: 0.9698616600790514 and parameters: {'n_estimators': 747, 'max_depth': 2, 'learning_rate': 0.32001440829474825, 'gamma': 0.0019126003149610587, 'min_child_weight': 1, 'subsample': 0.9707912347002509, 'colsample_bytree': 0.5423708785702983, 'reg_alpha': 5.966945807712596e-05, 'reg_lambda': 1.0493234578616303e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,248] Trial 180 finished with value: 0.9551535421100639 and parameters: {'n_estimators': 294, 'max_depth': 1, 'learning_rate': 0.3357416315742316, 'gamma': 0.007657877580656061, 'min_child_weight': 1, 'subsample': 0.9919818138814995, 'colsample_bytree': 0.5887452792406924, 'reg_alpha': 4.579238829952115e-05, 'reg_lambda': 0.0018385729955730126}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,341] Trial 181 finished with value: 0.9701226309921962 and parameters: {'n_estimators': 595, 'max_depth': 2, 'learning_rate': 0.3196711674185751, 'gamma': 0.004045724729064204, 'min_child_weight': 1, 'subsample': 0.9331559720774428, 'colsample_bytree': 0.5844164508168194, 'reg_alpha': 2.742025068307707e-05, 'reg_lambda': 0.009885387517462787}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,443] Trial 182 finished with value: 0.9688253775210296 and parameters: {'n_estimators': 571, 'max_depth': 2, 'learning_rate': 0.30577243814461674, 'gamma': 0.012880627685399902, 'min_child_weight': 1, 'subsample': 0.9485931009156126, 'colsample_bytree': 0.5996568259313692, 'reg_alpha': 1.3396606182173234e-05, 'reg_lambda': 0.007635969022558665}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,535] Trial 183 finished with value: 0.9674166413296849 and parameters: {'n_estimators': 629, 'max_depth': 3, 'learning_rate': 0.28188713644457714, 'gamma': 0.005235909540075137, 'min_child_weight': 1, 'subsample': 0.961053367499909, 'colsample_bytree': 0.6198251105511885, 'reg_alpha': 2.5215043925068256e-05, 'reg_lambda': 0.002628148822304905}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,589] Trial 184 finished with value: 0.9649437519002737 and parameters: {'n_estimators': 67, 'max_depth': 3, 'learning_rate': 0.35529559929163035, 'gamma': 0.001225158706094834, 'min_child_weight': 1, 'subsample': 0.9338994225805587, 'colsample_bytree': 0.5674075089505664, 'reg_alpha': 0.08714908351909771, 'reg_lambda': 0.004961439672981354}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,681] Trial 185 finished with value: 0.965017229147664 and parameters: {'n_estimators': 607, 'max_depth': 2, 'learning_rate': 0.3839038757913715, 'gamma': 0.002331336980927999, 'min_child_weight': 1, 'subsample': 0.9892104914873026, 'colsample_bytree': 0.5192707137105969, 'reg_alpha': 7.812769802730331e-05, 'reg_lambda': 0.033524561228580545}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,774] Trial 186 finished with value: 0.9667148069321984 and parameters: {'n_estimators': 835, 'max_depth': 6, 'learning_rate': 0.3428772238998707, 'gamma': 0.004906203351066525, 'min_child_weight': 1, 'subsample': 0.9769488668693691, 'colsample_bytree': 0.5510092209217737, 'reg_alpha': 0.00013871818028374805, 'reg_lambda': 0.01985471270961442}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,841] Trial 187 finished with value: 0.9673913043478259 and parameters: {'n_estimators': 253, 'max_depth': 4, 'learning_rate': 0.32508797810579004, 'gamma': 0.0009561938888235766, 'min_child_weight': 1, 'subsample': 0.9161395624008124, 'colsample_bytree': 0.9607189113456386, 'reg_alpha': 9.607969314415795e-06, 'reg_lambda': 1.3099693721755294e-05}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,920] Trial 188 finished with value: 0.9691547582851932 and parameters: {'n_estimators': 546, 'max_depth': 5, 'learning_rate': 0.295502717565899, 'gamma': 0.009464505555965745, 'min_child_weight': 1, 'subsample': 0.9248654467114628, 'colsample_bytree': 0.5093090629574039, 'reg_alpha': 3.311414049778045e-05, 'reg_lambda': 0.011358963682681302}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:55,999] Trial 189 finished with value: 0.9682755650146954 and parameters: {'n_estimators': 640, 'max_depth': 8, 'learning_rate': 0.3600401699105416, 'gamma': 8.633600075102984e-07, 'min_child_weight': 7, 'subsample': 0.9529371337244095, 'colsample_bytree': 0.5793876812256805, 'reg_alpha': 1.854830942484543e-05, 'reg_lambda': 0.0071807775805754264}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,077] Trial 190 finished with value: 0.9641785750481402 and parameters: {'n_estimators': 580, 'max_depth': 1, 'learning_rate': 0.3955258955416034, 'gamma': 0.0028855432380126994, 'min_child_weight': 1, 'subsample': 0.6558300232658375, 'colsample_bytree': 0.532053023783299, 'reg_alpha': 5.025989847819503e-05, 'reg_lambda': 0.0003699564761924533}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,170] Trial 191 finished with value: 0.9765556906861255 and parameters: {'n_estimators': 575, 'max_depth': 8, 'learning_rate': 0.36859695453147573, 'gamma': 0.00017562327914148257, 'min_child_weight': 1, 'subsample': 0.9949295139298673, 'colsample_bytree': 0.504238342895176, 'reg_alpha': 5.494592850652422e-06, 'reg_lambda': 0.05999590732038283}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,260] Trial 192 finished with value: 0.9762187088274045 and parameters: {'n_estimators': 597, 'max_depth': 8, 'learning_rate': 0.37669387399080473, 'gamma': 0.0001054246260196604, 'min_child_weight': 1, 'subsample': 0.9911385292858662, 'colsample_bytree': 0.5008474674992347, 'reg_alpha': 3.775728586579843e-06, 'reg_lambda': 0.06070795069378114}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,338] Trial 193 finished with value: 0.9697603121516163 and parameters: {'n_estimators': 565, 'max_depth': 8, 'learning_rate': 0.3733367211586875, 'gamma': 0.00010171868639087341, 'min_child_weight': 1, 'subsample': 0.9885402527271766, 'colsample_bytree': 0.503296796362895, 'reg_alpha': 3.156842485650543e-06, 'reg_lambda': 0.10114525177731656}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,432] Trial 194 finished with value: 0.9722965440356746 and parameters: {'n_estimators': 618, 'max_depth': 9, 'learning_rate': 0.36465218306972474, 'gamma': 0.000132198680326127, 'min_child_weight': 1, 'subsample': 0.9998270693902586, 'colsample_bytree': 0.5003410098501623, 'reg_alpha': 5.171884685209688e-06, 'reg_lambda': 0.048537409450488525}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,524] Trial 195 finished with value: 0.9762187088274045 and parameters: {'n_estimators': 699, 'max_depth': 8, 'learning_rate': 0.3840175223825088, 'gamma': 2.8688603044497538e-05, 'min_child_weight': 1, 'subsample': 0.9791585243331079, 'colsample_bytree': 0.5177740106795239, 'reg_alpha': 1.985570244508912e-06, 'reg_lambda': 0.0850937565995448}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,616] Trial 196 finished with value: 0.9731351981351981 and parameters: {'n_estimators': 704, 'max_depth': 8, 'learning_rate': 0.3845510622747572, 'gamma': 3.2293045599745385e-05, 'min_child_weight': 1, 'subsample': 0.9708751000446808, 'colsample_bytree': 0.5160888376342883, 'reg_alpha': 1.1285147244308468e-06, 'reg_lambda': 0.07777113981412653}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,707] Trial 197 finished with value: 0.9740194588020676 and parameters: {'n_estimators': 686, 'max_depth': 7, 'learning_rate': 0.3807493855934895, 'gamma': 4.962483143323837e-05, 'min_child_weight': 1, 'subsample': 0.9825848909958048, 'colsample_bytree': 0.5164570385938616, 'reg_alpha': 2.365763358102613e-06, 'reg_lambda': 0.13749590646470938}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,799] Trial 198 finished with value: 0.9669251038816256 and parameters: {'n_estimators': 679, 'max_depth': 7, 'learning_rate': 0.39587927481041185, 'gamma': 6.076559520990681e-06, 'min_child_weight': 2, 'subsample': 0.980027070691821, 'colsample_bytree': 0.5121661148934848, 'reg_alpha': 2.1636220457836166e-06, 'reg_lambda': 0.1981344625178931}. Best is trial 87 with value: 0.9775793047532177.\n", + "[I 2025-08-18 23:04:56,894] Trial 199 finished with value: 0.9730085132259045 and parameters: {'n_estimators': 734, 'max_depth': 8, 'learning_rate': 0.3827459493351444, 'gamma': 5.577111965000543e-05, 'min_child_weight': 1, 'subsample': 0.9874622359136933, 'colsample_bytree': 0.524715757741188, 'reg_alpha': 2.583619561021487e-06, 'reg_lambda': 0.12564000314896498}. Best is trial 87 with value: 0.9775793047532177.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best trial:\n", + "F1 Score: 0.977579\n", + "Parameters:\n", + "n_estimators: 636\n", + "max_depth: 3\n", + "learning_rate: 0.28911459468011935\n", + "gamma: 0.0026877179567177173\n", + "min_child_weight: 1\n", + "subsample: 0.9884898945689472\n", + "colsample_bytree: 0.5529899112143574\n", + "reg_alpha: 8.780578569353003e-06\n", + "reg_lambda: 0.024175358439225716\n" + ] + } + ], + "source": [ + "import xgboost as xgb\n", + "\n", + "\n", + "def objective(trial):\n", + " params = {\n", + " \"objective\": \"binary:logistic\",\n", + " \"use_label_encoder\": False,\n", + " \"n_estimators\": trial.suggest_int(\"n_estimators\", 20, 1000),\n", + " \"max_depth\": trial.suggest_int(\"max_depth\", 1, 20),\n", + " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 0.7),\n", + " \"gamma\": trial.suggest_float(\"gamma\", 1e-8, 1.0, log=True),\n", + " \"min_child_weight\": trial.suggest_int(\"min_child_weight\", 1, 10),\n", + " \"subsample\": trial.suggest_float(\"subsample\", 0.5, 1.0),\n", + " \"colsample_bytree\": trial.suggest_float(\"colsample_bytree\", 0.5, 1.0),\n", + " \"reg_alpha\": trial.suggest_float(\"reg_alpha\", 1e-8, 1.0, log=True),\n", + " \"reg_lambda\": trial.suggest_float(\"reg_lambda\", 1e-8, 1.0, log=True),\n", + " \"enable_categorical\": True,\n", + " \"eval_metric\": \"logloss\",\n", + " }\n", + "\n", + " model = xgb.XGBClassifier(**params)\n", + "\n", + " scores = cross_val_score(\n", + " estimator=model,\n", + " X=X,\n", + " y=y,\n", + " scoring=\"f1_weighted\",\n", + " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", + " n_jobs=-1,\n", + " )\n", + "\n", + " return scores.mean()\n", + "\n", + "\n", + "study = optuna.create_study(direction=\"maximize\")\n", + "study.optimize(objective, n_trials=200)\n", + "\n", + "best_trial = study.best_trial\n", + "\n", + "print(\"Best trial:\")\n", + "print(f\"F1 Score: {best_trial.value:.6f}\")\n", + "print(\"Parameters:\")\n", + "for k, v in best_trial.params.items():\n", + " print(f\"{k}: {v}\")" + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "[I 2025-08-17 17:05:16,870] A new study created in memory with name: no-name-58367467-9a1e-4d65-bfaf-46562a4f4de8\n", - "[I 2025-08-17 17:05:17,646] Trial 0 finished with value: 0.9336826514116986 and parameters: {'iterations': 447, 'depth': 7, 'learning_rate': 0.010022052741993987, 'l2_leaf_reg': 0.00012108855576002585, 'random_strength': 0.0014307171606371407, 'bagging_temperature': 1.2400472888236214, 'border_count': 118, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 67, 'rsm': 0.7492964415768959}. Best is trial 0 with value: 0.9336826514116986.\n", - "[I 2025-08-17 17:05:28,392] Trial 1 finished with value: 0.9357671816047922 and parameters: {'iterations': 320, 'depth': 12, 'learning_rate': 0.005265584834540258, 'l2_leaf_reg': 3.348332251065364e-05, 'random_strength': 0.016130126681163013, 'bagging_temperature': 3.184610728695145, 'border_count': 132, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 16, 'rsm': 0.3661804580910256}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:05:56,176] Trial 2 finished with value: 0.9353286370472839 and parameters: {'iterations': 301, 'depth': 15, 'learning_rate': 0.001229239587857227, 'l2_leaf_reg': 0.24114858700166839, 'random_strength': 3.653421601255403e-08, 'bagging_temperature': 0.268499084758938, 'border_count': 38, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 87, 'rsm': 0.4077894430643999}. Best is trial 1 with value: 0.9357671816047922.\n", - "/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/joblib/externals/loky/process_executor.py:782: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n", - " warnings.warn(\n", - "[I 2025-08-17 17:05:59,001] Trial 3 finished with value: 0.9263914470949277 and parameters: {'iterations': 308, 'depth': 8, 'learning_rate': 0.006923745139831324, 'l2_leaf_reg': 2.232447055025466e-05, 'random_strength': 9.589017869992023, 'bagging_temperature': 1.1664981735070379, 'border_count': 244, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 36, 'rsm': 0.2272363033800584}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:05:59,894] Trial 4 finished with value: 0.9307067517478776 and parameters: {'iterations': 384, 'depth': 2, 'learning_rate': 0.006162982787165949, 'l2_leaf_reg': 0.0002455528925686078, 'random_strength': 0.00023861190911366858, 'bagging_temperature': 4.590603297409774, 'border_count': 89, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 43, 'rsm': 0.47744937225955014}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:09:58,626] Trial 5 finished with value: 0.9211242467721258 and parameters: {'iterations': 126, 'depth': 16, 'learning_rate': 0.009746370340105637, 'l2_leaf_reg': 0.00030954644505648175, 'random_strength': 2.429275544391415e-05, 'bagging_temperature': 2.010716645408075, 'border_count': 49, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 13, 'rsm': 0.9165484726032328}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:10:00,013] Trial 6 finished with value: 0.9279980893054489 and parameters: {'iterations': 304, 'depth': 13, 'learning_rate': 0.002452909941863272, 'l2_leaf_reg': 0.0007960036275127577, 'random_strength': 0.03279083919638105, 'bagging_temperature': 0.11620956490151985, 'border_count': 176, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 90, 'rsm': 0.4918546771049915}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:10:00,157] Trial 7 finished with value: 0.9033264977789675 and parameters: {'iterations': 118, 'depth': 6, 'learning_rate': 0.0010815676236105107, 'l2_leaf_reg': 2.343577077870732e-06, 'random_strength': 0.19573002126091082, 'bagging_temperature': 9.328816805466154, 'border_count': 92, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 73, 'rsm': 0.7721304474012315}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:10:01,029] Trial 8 finished with value: 0.9282028882177922 and parameters: {'iterations': 139, 'depth': 13, 'learning_rate': 0.37449386293043335, 'l2_leaf_reg': 1.510385273200855e-07, 'random_strength': 8.805885915613816e-06, 'bagging_temperature': 9.920620684320985, 'border_count': 103, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 82, 'rsm': 0.7133460589949088}. Best is trial 1 with value: 0.9357671816047922.\n", - "[I 2025-08-17 17:10:01,332] Trial 9 finished with value: 0.9478823107512284 and parameters: {'iterations': 442, 'depth': 14, 'learning_rate': 0.017390550482273417, 'l2_leaf_reg': 1.4191517744514907e-08, 'random_strength': 0.08085481833131353, 'bagging_temperature': 0.5861540758081338, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.3057024492058511}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:01,540] Trial 10 finished with value: 0.9387675439474699 and parameters: {'iterations': 483, 'depth': 10, 'learning_rate': 0.06649646241149486, 'l2_leaf_reg': 1.5294498702948475e-08, 'random_strength': 6.457056903771226, 'bagging_temperature': 0.3762360484331467, 'border_count': 185, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 60, 'rsm': 0.1129456685393378}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:01,745] Trial 11 finished with value: 0.9364695961754009 and parameters: {'iterations': 488, 'depth': 10, 'learning_rate': 0.07157332063575793, 'l2_leaf_reg': 1.2340552291844822e-08, 'random_strength': 6.8475165988578945, 'bagging_temperature': 0.41833481531429084, 'border_count': 183, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 57, 'rsm': 0.12225677733328608}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:01,879] Trial 12 finished with value: 0.9420281633568404 and parameters: {'iterations': 401, 'depth': 10, 'learning_rate': 0.04705474327284803, 'l2_leaf_reg': 4.619135274034043e-08, 'random_strength': 0.2877962903926624, 'bagging_temperature': 0.4410061869425525, 'border_count': 183, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.10497821047560195}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:02,057] Trial 13 finished with value: 0.9392165631469979 and parameters: {'iterations': 401, 'depth': 4, 'learning_rate': 0.035092587572258575, 'l2_leaf_reg': 7.418402902502616e-07, 'random_strength': 0.24279060329838162, 'bagging_temperature': 0.550265277142082, 'border_count': 223, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.2912361775318139}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:02,163] Trial 14 finished with value: 0.9332145859168754 and parameters: {'iterations': 196, 'depth': 11, 'learning_rate': 0.20424392007978667, 'l2_leaf_reg': 0.07259273690884574, 'random_strength': 0.445044262919236, 'bagging_temperature': 0.16497562046877015, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.2189011845729476}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:02,465] Trial 15 finished with value: 0.942245284348707 and parameters: {'iterations': 396, 'depth': 14, 'learning_rate': 0.023781291427423204, 'l2_leaf_reg': 9.270565187606277, 'random_strength': 0.0038796338897692183, 'bagging_temperature': 0.6361579144475542, 'border_count': 205, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 77, 'rsm': 0.29776900392803746}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:02,727] Trial 16 finished with value: 0.9394832914849566 and parameters: {'iterations': 234, 'depth': 14, 'learning_rate': 0.025406716067111187, 'l2_leaf_reg': 0.00940902288686199, 'random_strength': 0.0011467692702004809, 'bagging_temperature': 0.9288491682156569, 'border_count': 217, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 79, 'rsm': 0.3312745395954699}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:03,328] Trial 17 finished with value: 0.9364990440949738 and parameters: {'iterations': 364, 'depth': 16, 'learning_rate': 0.01459315336705923, 'l2_leaf_reg': 1.5017720263656562, 'random_strength': 2.168129156965766e-07, 'bagging_temperature': 0.7031608622072022, 'border_count': 161, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 68, 'rsm': 0.579429591294561}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:04,579] Trial 18 finished with value: 0.9336769052166423 and parameters: {'iterations': 437, 'depth': 14, 'learning_rate': 0.09335993870933126, 'l2_leaf_reg': 0.009070739751415742, 'random_strength': 0.011596516896850755, 'bagging_temperature': 0.21831142466765102, 'border_count': 217, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 31, 'rsm': 0.6254526681385288}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:04,966] Trial 19 finished with value: 0.9452204073242001 and parameters: {'iterations': 345, 'depth': 12, 'learning_rate': 0.018942551364461224, 'l2_leaf_reg': 7.3406357956098915, 'random_strength': 7.810547328849867e-05, 'bagging_temperature': 2.592739930745042, 'border_count': 254, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 51, 'rsm': 0.2411083987489646}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:05,836] Trial 20 finished with value: 0.9416257250171322 and parameters: {'iterations': 238, 'depth': 12, 'learning_rate': 0.16297331414932478, 'l2_leaf_reg': 3.20532030293621e-06, 'random_strength': 2.667508753112458e-05, 'bagging_temperature': 1.9944880335976674, 'border_count': 248, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 1, 'rsm': 0.19965980630801725}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:06,233] Trial 21 finished with value: 0.9394580121286875 and parameters: {'iterations': 354, 'depth': 14, 'learning_rate': 0.021032869203904486, 'l2_leaf_reg': 8.092710664822752, 'random_strength': 0.0001705884950621921, 'bagging_temperature': 2.0769627719799915, 'border_count': 204, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 50, 'rsm': 0.2886138656825273}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:06,725] Trial 22 finished with value: 0.9422897581604335 and parameters: {'iterations': 427, 'depth': 12, 'learning_rate': 0.01728066242461722, 'l2_leaf_reg': 8.28487233199894, 'random_strength': 2.149716909747561e-06, 'bagging_temperature': 0.8352506132748097, 'border_count': 251, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 75, 'rsm': 0.42775896559818366}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:06,823] Trial 23 finished with value: 0.9278465391707099 and parameters: {'iterations': 54, 'depth': 9, 'learning_rate': 0.0034815878598868596, 'l2_leaf_reg': 0.5205208963206108, 'random_strength': 1.4520874032939126e-06, 'bagging_temperature': 4.7210870436758015, 'border_count': 255, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 56, 'rsm': 0.4280559895016039}. Best is trial 9 with value: 0.9478823107512284.\n", - "[I 2025-08-17 17:10:07,101] Trial 24 finished with value: 0.9479595700629927 and parameters: {'iterations': 439, 'depth': 11, 'learning_rate': 0.014527673079264242, 'l2_leaf_reg': 0.04052582749131081, 'random_strength': 7.707152529842055e-07, 'bagging_temperature': 1.0117939040088955, 'border_count': 66, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 66, 'rsm': 0.5153902213295005}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:07,491] Trial 25 finished with value: 0.9363015933085312 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.011466713691318525, 'l2_leaf_reg': 0.07842092575522967, 'random_strength': 1.622972705803686e-08, 'bagging_temperature': 1.328255947976371, 'border_count': 67, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 48, 'rsm': 0.536170510768572}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:07,817] Trial 26 finished with value: 0.9335191724299957 and parameters: {'iterations': 461, 'depth': 9, 'learning_rate': 0.0429759330516577, 'l2_leaf_reg': 0.004048148753961586, 'random_strength': 3.7632379882557923e-07, 'bagging_temperature': 3.403927830806352, 'border_count': 69, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 64, 'rsm': 0.6525305409485735}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:08,358] Trial 27 finished with value: 0.9282013843144794 and parameters: {'iterations': 350, 'depth': 6, 'learning_rate': 0.003882869945542356, 'l2_leaf_reg': 0.05588647211639355, 'random_strength': 6.359930947232507e-05, 'bagging_temperature': 1.4592262498420976, 'border_count': 131, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 34, 'rsm': 0.9793885580992495}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:08,548] Trial 28 finished with value: 0.9420309049149707 and parameters: {'iterations': 425, 'depth': 11, 'learning_rate': 0.029726236281782142, 'l2_leaf_reg': 1.5338456392901354, 'random_strength': 3.743821948231872e-06, 'bagging_temperature': 2.9080001491398706, 'border_count': 62, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 44, 'rsm': 0.17938436731862395}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:08,873] Trial 29 finished with value: 0.9422389645096398 and parameters: {'iterations': 464, 'depth': 13, 'learning_rate': 0.009239537495248366, 'l2_leaf_reg': 0.0016581052501387665, 'random_strength': 0.0010903132600641387, 'bagging_temperature': 5.8823898983566085, 'border_count': 117, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 68, 'rsm': 0.369621859571436}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:09,187] Trial 30 finished with value: 0.9396483121154722 and parameters: {'iterations': 330, 'depth': 8, 'learning_rate': 0.014443547745130356, 'l2_leaf_reg': 1.439392094711217, 'random_strength': 3.739301341196257e-07, 'bagging_temperature': 0.308963668790458, 'border_count': 111, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 85, 'rsm': 0.8015034073072183}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:09,647] Trial 31 finished with value: 0.9364292909269782 and parameters: {'iterations': 431, 'depth': 12, 'learning_rate': 0.016172687028915955, 'l2_leaf_reg': 9.851796326883738, 'random_strength': 1.5263901772318894e-06, 'bagging_temperature': 0.8713768131029922, 'border_count': 236, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 71, 'rsm': 0.46762344504636993}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 17:10:10,098] Trial 32 finished with value: 0.9420281633568404 and parameters: {'iterations': 422, 'depth': 12, 'learning_rate': 0.019237803571276867, 'l2_leaf_reg': 5.64247056264795e-05, 'random_strength': 1.110832663151052e-07, 'bagging_temperature': 0.769726648591094, 'border_count': 234, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 62, 'rsm': 0.3888529760016267}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:57:45,302] Trial 33 finished with value: 0.938692385540542 and parameters: {'iterations': 463, 'depth': 15, 'learning_rate': 0.009645280889137171, 'l2_leaf_reg': 0.35813648095480866, 'random_strength': 2.6469075432648367e-06, 'bagging_temperature': 0.5215296142925352, 'border_count': 130, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 76, 'rsm': 0.5297182093386201}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:57:46,696] Trial 34 finished with value: 0.941986075759133 and parameters: {'iterations': 382, 'depth': 15, 'learning_rate': 0.007461286652302521, 'l2_leaf_reg': 0.045944207061274785, 'random_strength': 1.1780126052966517e-05, 'bagging_temperature': 1.1591340186781007, 'border_count': 35, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 54, 'rsm': 0.4292186056059847}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:57:54,557] Trial 35 finished with value: 0.938692385540542 and parameters: {'iterations': 323, 'depth': 12, 'learning_rate': 0.005100615830139832, 'l2_leaf_reg': 2.76900031010676, 'random_strength': 4.188228359346592e-08, 'bagging_temperature': 1.747951669619372, 'border_count': 146, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 91, 'rsm': 0.26684788997918296}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:57:55,361] Trial 36 finished with value: 0.9302795905288737 and parameters: {'iterations': 253, 'depth': 1, 'learning_rate': 0.039079338269258676, 'l2_leaf_reg': 0.3264818328644774, 'random_strength': 0.0001884997641458613, 'bagging_temperature': 2.7785286733195584, 'border_count': 201, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 65, 'rsm': 0.583038894597953}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:58:22,055] Trial 37 finished with value: 0.9388894809828734 and parameters: {'iterations': 280, 'depth': 13, 'learning_rate': 0.014094418061125095, 'l2_leaf_reg': 3.908286333679212, 'random_strength': 8.958686737872702e-05, 'bagging_temperature': 1.032578356936754, 'border_count': 237, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 42, 'rsm': 0.3272909714423266}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:58:23,234] Trial 38 finished with value: 0.9364990440949738 and parameters: {'iterations': 365, 'depth': 11, 'learning_rate': 0.060059916793946344, 'l2_leaf_reg': 7.868576296018248e-06, 'random_strength': 6.792612118084799e-07, 'bagging_temperature': 1.5912784757409366, 'border_count': 166, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.4652304438594406}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 18:58:24,209] Trial 39 finished with value: 0.9366516728480241 and parameters: {'iterations': 446, 'depth': 7, 'learning_rate': 0.002658865746535032, 'l2_leaf_reg': 0.00011552756384141058, 'random_strength': 0.0005168873823892629, 'bagging_temperature': 0.2564675614174855, 'border_count': 79, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 83, 'rsm': 0.16741994023948076}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:40,334] Trial 40 finished with value: 0.9145144021182363 and parameters: {'iterations': 416, 'depth': 16, 'learning_rate': 0.001625377939477702, 'l2_leaf_reg': 0.01695192283696182, 'random_strength': 1.2800588262812822, 'bagging_temperature': 2.460206131631878, 'border_count': 44, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 28, 'rsm': 0.35901664766904245}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:42,002] Trial 41 finished with value: 0.9392165631469979 and parameters: {'iterations': 389, 'depth': 15, 'learning_rate': 0.025079439069078373, 'l2_leaf_reg': 0.6243249540865272, 'random_strength': 0.006997599154730658, 'bagging_temperature': 0.5911520319919781, 'border_count': 198, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.25415982233413037}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:42,934] Trial 42 finished with value: 0.9392165631469979 and parameters: {'iterations': 406, 'depth': 13, 'learning_rate': 0.02054123087754466, 'l2_leaf_reg': 3.919564761634939, 'random_strength': 0.055677410426894, 'bagging_temperature': 0.6517074553530903, 'border_count': 225, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 77, 'rsm': 0.3298616390415405}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:43,845] Trial 43 finished with value: 0.942125092874029 and parameters: {'iterations': 378, 'depth': 14, 'learning_rate': 0.007026342264096326, 'l2_leaf_reg': 8.711730483641022, 'random_strength': 0.00472664123555551, 'bagging_temperature': 0.3446434221110068, 'border_count': 255, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.4312689437069658}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:44,922] Trial 44 finished with value: 0.9450707105413858 and parameters: {'iterations': 473, 'depth': 10, 'learning_rate': 0.027681440661557893, 'l2_leaf_reg': 0.18291973999173342, 'random_strength': 0.00325240166416229, 'bagging_temperature': 0.4897789674798157, 'border_count': 210, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.4990356400478725}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:45,274] Trial 45 finished with value: 0.9448535895495193 and parameters: {'iterations': 479, 'depth': 10, 'learning_rate': 0.029930321385175925, 'l2_leaf_reg': 0.18263997781920413, 'random_strength': 7.949010143906268e-06, 'bagging_temperature': 0.4895403089803191, 'border_count': 96, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.5238484162127857}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:45,768] Trial 46 finished with value: 0.9364356107660455 and parameters: {'iterations': 482, 'depth': 10, 'learning_rate': 0.10487991736828609, 'l2_leaf_reg': 0.14015721097061587, 'random_strength': 0.06871745384141728, 'bagging_temperature': 0.498601333720442, 'border_count': 92, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 59, 'rsm': 0.718638239457858}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:46,074] Trial 47 finished with value: 0.9363079131475986 and parameters: {'iterations': 474, 'depth': 9, 'learning_rate': 0.05448482436597816, 'l2_leaf_reg': 0.0007508312150194058, 'random_strength': 1.979400992759582e-05, 'bagging_temperature': 0.21002891587474082, 'border_count': 53, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 70, 'rsm': 0.6263174952857236}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:46,353] Trial 48 finished with value: 0.936230298491723 and parameters: {'iterations': 449, 'depth': 7, 'learning_rate': 0.03372017360451665, 'l2_leaf_reg': 0.02508232620466937, 'random_strength': 0.02516944698482475, 'bagging_temperature': 0.40295412254807156, 'border_count': 78, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 53, 'rsm': 0.5170308825970374}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:46,687] Trial 49 finished with value: 0.9448535895495193 and parameters: {'iterations': 491, 'depth': 10, 'learning_rate': 0.029047803839886373, 'l2_leaf_reg': 0.12411530275943795, 'random_strength': 8.287968664356238e-06, 'bagging_temperature': 0.46420002877368444, 'border_count': 99, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.576394702785206}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:47,079] Trial 50 finished with value: 0.9335149171108468 and parameters: {'iterations': 449, 'depth': 8, 'learning_rate': 0.012384714014048469, 'l2_leaf_reg': 4.3977186402650976e-07, 'random_strength': 0.002271373832260034, 'bagging_temperature': 0.1043542172721108, 'border_count': 82, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 61, 'rsm': 0.8253111118684651}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:47,501] Trial 51 finished with value: 0.9452420510109686 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.03232589786063133, 'l2_leaf_reg': 0.19703798265346817, 'random_strength': 5.682342586106171e-06, 'bagging_temperature': 0.4457314732827191, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.5727499927098123}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:48,019] Trial 52 finished with value: 0.9448457718455867 and parameters: {'iterations': 499, 'depth': 11, 'learning_rate': 0.08201361984215827, 'l2_leaf_reg': 0.002668078344401463, 'random_strength': 7.629588890045705e-06, 'bagging_temperature': 0.37097420807829845, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 86, 'rsm': 0.6786931996465365}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:48,422] Trial 53 finished with value: 0.9451013583702761 and parameters: {'iterations': 476, 'depth': 11, 'learning_rate': 0.04256451322092073, 'l2_leaf_reg': 0.18609798645826242, 'random_strength': 4.354965293869604e-05, 'bagging_temperature': 0.2870688189555022, 'border_count': 118, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.4929604048578121}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:48,908] Trial 54 finished with value: 0.9422897581604335 and parameters: {'iterations': 464, 'depth': 13, 'learning_rate': 0.04639776081891739, 'l2_leaf_reg': 0.7666153446391908, 'random_strength': 7.476609311900428e-05, 'bagging_temperature': 0.18093394455307654, 'border_count': 122, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.4812218350798194}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:49,360] Trial 55 finished with value: 0.9420419893396765 and parameters: {'iterations': 444, 'depth': 11, 'learning_rate': 0.12177647073574174, 'l2_leaf_reg': 0.025253511131175507, 'random_strength': 0.0004968302143202226, 'bagging_temperature': 0.29574922923916513, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.5800214751972506}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:49,481] Trial 56 finished with value: 0.9303835174168823 and parameters: {'iterations': 179, 'depth': 9, 'learning_rate': 0.4804592339834937, 'l2_leaf_reg': 4.29374260688016e-08, 'random_strength': 2.1023104425356554e-05, 'bagging_temperature': 0.15252719973624834, 'border_count': 189, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.23538528068494383}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:49,935] Trial 57 finished with value: 0.9391606495664544 and parameters: {'iterations': 409, 'depth': 12, 'learning_rate': 0.03858242532556046, 'l2_leaf_reg': 0.0005243163656055302, 'random_strength': 0.90882557493314, 'bagging_temperature': 0.2467396953084091, 'border_count': 172, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.6205511157155944}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:50,111] Trial 58 finished with value: 0.9450568845585497 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.022903344954733652, 'l2_leaf_reg': 0.0050895313793075285, 'random_strength': 3.959400177014319e-05, 'bagging_temperature': 7.691139508185991, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.14328631200347425}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:50,358] Trial 59 finished with value: 0.9449614966901738 and parameters: {'iterations': 288, 'depth': 10, 'learning_rate': 0.052270626553195046, 'l2_leaf_reg': 0.015183999507432818, 'random_strength': 0.0003193911671015348, 'bagging_temperature': 0.7215808592563201, 'border_count': 158, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.5051907715975001}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:50,626] Trial 60 finished with value: 0.9392610369587242 and parameters: {'iterations': 337, 'depth': 12, 'learning_rate': 0.07355185141560906, 'l2_leaf_reg': 0.20196677808219077, 'random_strength': 9.173337953915923e-07, 'bagging_temperature': 1.076397502882221, 'border_count': 139, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.5483613280711558}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:50,786] Trial 61 finished with value: 0.9450568845585497 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.022503958124257865, 'l2_leaf_reg': 0.0053822010708529785, 'random_strength': 3.6788525900741224e-06, 'bagging_temperature': 8.340087130052538, 'border_count': 110, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.14046713436027425}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:51,001] Trial 62 finished with value: 0.9450568845585497 and parameters: {'iterations': 458, 'depth': 11, 'learning_rate': 0.01689186112137248, 'l2_leaf_reg': 0.05213905679989868, 'random_strength': 5.761360055878985e-05, 'bagging_temperature': 3.8785298751967336, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 84, 'rsm': 0.21604658939588595}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:51,151] Trial 63 finished with value: 0.9451013583702761 and parameters: {'iterations': 489, 'depth': 4, 'learning_rate': 0.0109998556655596, 'l2_leaf_reg': 0.0015933889574844828, 'random_strength': 3.7107547701043355e-05, 'bagging_temperature': 0.5750351844280351, 'border_count': 112, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.17440247613480278}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:51,325] Trial 64 finished with value: 0.9394580121286875 and parameters: {'iterations': 497, 'depth': 4, 'learning_rate': 0.008862185692537406, 'l2_leaf_reg': 0.0001616306852051432, 'random_strength': 0.0001253545848135207, 'bagging_temperature': 0.5809952238061248, 'border_count': 87, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.39211824641718424}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:51,557] Trial 65 finished with value: 0.9450568845585497 and parameters: {'iterations': 441, 'depth': 4, 'learning_rate': 0.01927073249172679, 'l2_leaf_reg': 0.8886683537672693, 'random_strength': 0.0009200433649419209, 'bagging_temperature': 0.3258586539625712, 'border_count': 147, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 22, 'rsm': 0.25435277879936763}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:53,561] Trial 66 finished with value: 0.9330174904745441 and parameters: {'iterations': 431, 'depth': 8, 'learning_rate': 0.01121881943404954, 'l2_leaf_reg': 0.001891135856776816, 'random_strength': 0.10334570071942178, 'bagging_temperature': 0.3935708768450864, 'border_count': 215, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 90, 'rsm': 0.19210065058904802}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:54,625] Trial 67 finished with value: 0.9450147969608423 and parameters: {'iterations': 484, 'depth': 3, 'learning_rate': 0.00579402157241798, 'l2_leaf_reg': 0.35127082993071396, 'random_strength': 0.010864405142117882, 'bagging_temperature': 0.7519525888035951, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 67, 'rsm': 0.45408506228049234}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:55,591] Trial 68 finished with value: 0.9391606495664544 and parameters: {'iterations': 459, 'depth': 9, 'learning_rate': 0.012411149890886005, 'l2_leaf_reg': 1.6764351896435874e-05, 'random_strength': 1.310790266546465e-07, 'bagging_temperature': 0.45145858949881645, 'border_count': 55, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 46, 'rsm': 0.3014763801342136}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:56,469] Trial 69 finished with value: 0.9369181533853135 and parameters: {'iterations': 418, 'depth': 6, 'learning_rate': 0.008387464067222912, 'l2_leaf_reg': 0.08155285274527148, 'random_strength': 0.002509110127115399, 'bagging_temperature': 0.9268562138535151, 'border_count': 71, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.6003005382283918}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:56,572] Trial 70 finished with value: 0.9390625201399484 and parameters: {'iterations': 309, 'depth': 1, 'learning_rate': 0.03329871150014482, 'l2_leaf_reg': 2.2276605358743353, 'random_strength': 4.9898598389615e-06, 'bagging_temperature': 0.6419929476777696, 'border_count': 106, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 100, 'rsm': 0.49360370831141787}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:56,743] Trial 71 finished with value: 0.9392165631469979 and parameters: {'iterations': 471, 'depth': 10, 'learning_rate': 0.0252888738684369, 'l2_leaf_reg': 0.005017507709629204, 'random_strength': 2.440068851809699e-05, 'bagging_temperature': 6.3294777334946986, 'border_count': 114, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.14864350704014634}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:56,916] Trial 72 finished with value: 0.9420281633568404 and parameters: {'iterations': 488, 'depth': 12, 'learning_rate': 0.01827112156919407, 'l2_leaf_reg': 0.0014745826355574527, 'random_strength': 3.275792525199124e-05, 'bagging_temperature': 1.276778289508142, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.15087933871697753}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:57,089] Trial 73 finished with value: 0.9420281633568404 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.042064077989929866, 'l2_leaf_reg': 0.0074787463668816384, 'random_strength': 1.2921631502648065e-05, 'bagging_temperature': 6.807420909116351, 'border_count': 135, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 90, 'rsm': 0.11210268157392836}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:57,572] Trial 74 finished with value: 0.9392165631469979 and parameters: {'iterations': 453, 'depth': 13, 'learning_rate': 0.014324211383182505, 'l2_leaf_reg': 0.01112135218539427, 'random_strength': 4.1357270748163564e-05, 'bagging_temperature': 4.490330592421232, 'border_count': 242, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 39, 'rsm': 0.20919152340585995}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:57,991] Trial 75 finished with value: 0.9422897581604335 and parameters: {'iterations': 436, 'depth': 14, 'learning_rate': 0.02827315737020178, 'l2_leaf_reg': 0.03221556524852036, 'random_strength': 0.00011592539358124591, 'bagging_temperature': 0.2803768481383997, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.663939368673399}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:15:58,177] Trial 76 finished with value: 0.9450568845585497 and parameters: {'iterations': 498, 'depth': 5, 'learning_rate': 0.021987917437276475, 'l2_leaf_reg': 0.00028929465695989555, 'random_strength': 0.0004455219763426272, 'bagging_temperature': 0.5433075891499852, 'border_count': 100, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 86, 'rsm': 0.1814060619681274}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:00,880] Trial 77 finished with value: 0.9330813491825122 and parameters: {'iterations': 396, 'depth': 10, 'learning_rate': 0.01589601631670435, 'l2_leaf_reg': 0.0340153617396941, 'random_strength': 0.00022120378185857412, 'bagging_temperature': 0.8333005477979103, 'border_count': 108, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 79, 'rsm': 0.2740591686694898}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:02,054] Trial 78 finished with value: 0.9362630839917611 and parameters: {'iterations': 486, 'depth': 12, 'learning_rate': 0.01250814432155388, 'l2_leaf_reg': 0.08597019771125995, 'random_strength': 3.875658497816237, 'bagging_temperature': 2.027781613667445, 'border_count': 228, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.554428285548262}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:02,477] Trial 79 finished with value: 0.9332999610216076 and parameters: {'iterations': 470, 'depth': 13, 'learning_rate': 0.03479471943998336, 'l2_leaf_reg': 0.0011038001978353085, 'random_strength': 1.4623871246898063e-06, 'bagging_temperature': 8.298637491032066, 'border_count': 86, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 1, 'rsm': 0.10575314391531795}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:02,578] Trial 80 finished with value: 0.930715608357473 and parameters: {'iterations': 64, 'depth': 11, 'learning_rate': 0.009970381997329417, 'l2_leaf_reg': 0.002457657979958449, 'random_strength': 5.006664611985971e-07, 'bagging_temperature': 0.3480378302514736, 'border_count': 195, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 83, 'rsm': 0.35085888320037617}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:02,759] Trial 81 finished with value: 0.939247210975888 and parameters: {'iterations': 474, 'depth': 11, 'learning_rate': 0.023021073395322878, 'l2_leaf_reg': 0.00501303583428343, 'random_strength': 3.297609176261554e-06, 'bagging_temperature': 9.116387247059526, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.1602471439901559}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:02,945] Trial 82 finished with value: 0.9422759321775974 and parameters: {'iterations': 455, 'depth': 11, 'learning_rate': 0.021341812343129634, 'l2_leaf_reg': 0.0032786030922662217, 'random_strength': 5.6167075068437285e-06, 'bagging_temperature': 7.001846826723126, 'border_count': 93, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.23565806187990584}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:03,131] Trial 83 finished with value: 0.9450568845585497 and parameters: {'iterations': 486, 'depth': 9, 'learning_rate': 0.025481031559351847, 'l2_leaf_reg': 0.00044861252069219073, 'random_strength': 1.3602639637159673e-05, 'bagging_temperature': 5.269525570746078, 'border_count': 210, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.12292909475376332}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:03,339] Trial 84 finished with value: 0.9421893707681634 and parameters: {'iterations': 467, 'depth': 10, 'learning_rate': 0.017194280312834556, 'l2_leaf_reg': 0.007334290737691393, 'random_strength': 2.3345258144382588e-06, 'bagging_temperature': 7.5185445722122735, 'border_count': 128, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 57, 'rsm': 0.14168837872160733}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:03,649] Trial 85 finished with value: 0.9391606495664544 and parameters: {'iterations': 436, 'depth': 10, 'learning_rate': 0.06135057142926861, 'l2_leaf_reg': 0.015040042311610397, 'random_strength': 3.579764468234165e-05, 'bagging_temperature': 9.828877956015381, 'border_count': 121, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 51, 'rsm': 0.3120321567349598}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:03,749] Trial 86 finished with value: 0.9334278799514462 and parameters: {'iterations': 255, 'depth': 2, 'learning_rate': 0.010786695590314385, 'l2_leaf_reg': 0.24367622394113866, 'random_strength': 8.993969123072843e-07, 'bagging_temperature': 5.586430695006047, 'border_count': 134, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 93, 'rsm': 0.44661208004691777}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:03,883] Trial 87 finished with value: 0.9420281633568404 and parameters: {'iterations': 422, 'depth': 12, 'learning_rate': 0.029876299308035606, 'l2_leaf_reg': 0.5101805055124192, 'random_strength': 1.6028254589219494e-05, 'bagging_temperature': 2.347165672173358, 'border_count': 74, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.13709507722446973}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:04,057] Trial 88 finished with value: 0.9420281633568404 and parameters: {'iterations': 500, 'depth': 12, 'learning_rate': 0.04807108394354161, 'l2_leaf_reg': 0.13790292373355792, 'random_strength': 2.632778506093437e-07, 'bagging_temperature': 3.569452748252071, 'border_count': 65, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.17151325317899663}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:04,169] Trial 89 finished with value: 0.9392610369587242 and parameters: {'iterations': 209, 'depth': 11, 'learning_rate': 0.013899379180866756, 'l2_leaf_reg': 1.1783486548788338, 'random_strength': 5.439814781017007e-05, 'bagging_temperature': 0.42528108214495586, 'border_count': 113, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 90, 'rsm': 0.20735459506567905}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:09,781] Trial 90 finished with value: 0.9270999046522576 and parameters: {'iterations': 478, 'depth': 9, 'learning_rate': 0.037845787355695625, 'l2_leaf_reg': 2.6515688541607453e-06, 'random_strength': 0.00010733387818114766, 'bagging_temperature': 0.22473932776660133, 'border_count': 174, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 78, 'rsm': 0.5545889385122719}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:10,910] Trial 91 finished with value: 0.9420281633568404 and parameters: {'iterations': 457, 'depth': 11, 'learning_rate': 0.01687742839839296, 'l2_leaf_reg': 0.058337034137483715, 'random_strength': 6.0975438635664064e-05, 'bagging_temperature': 3.8481206713620297, 'border_count': 121, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 85, 'rsm': 0.23247169942382973}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:11,158] Trial 92 finished with value: 0.942245284348707 and parameters: {'iterations': 445, 'depth': 11, 'learning_rate': 0.020355212143055232, 'l2_leaf_reg': 0.051207521743224876, 'random_strength': 4.4117960211688904e-06, 'bagging_temperature': 4.116640848888592, 'border_count': 126, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 84, 'rsm': 0.21191224274175083}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:12,071] Trial 93 finished with value: 0.9392165631469979 and parameters: {'iterations': 464, 'depth': 10, 'learning_rate': 0.026718910027624717, 'l2_leaf_reg': 0.021701446878278626, 'random_strength': 0.0003112530044111786, 'bagging_temperature': 8.294352455693376, 'border_count': 100, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 64, 'rsm': 0.19123093114228457}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:12,954] Trial 94 finished with value: 0.9420281633568404 and parameters: {'iterations': 489, 'depth': 11, 'learning_rate': 0.014921326317568194, 'l2_leaf_reg': 0.10684023710190069, 'random_strength': 0.00015629124932698926, 'bagging_temperature': 1.5913711380912872, 'border_count': 108, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.12680316028591293}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:13,154] Trial 95 finished with value: 0.9422897581604335 and parameters: {'iterations': 366, 'depth': 15, 'learning_rate': 0.007724090791156113, 'l2_leaf_reg': 4.970487705297225, 'random_strength': 4.832812376313844e-05, 'bagging_temperature': 2.996806980720935, 'border_count': 118, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 91, 'rsm': 0.25001746171887856}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:13,408] Trial 96 finished with value: 0.9478629958899154 and parameters: {'iterations': 454, 'depth': 13, 'learning_rate': 0.03206259992239698, 'l2_leaf_reg': 9.747885664977631e-07, 'random_strength': 0.0007036688892877016, 'bagging_temperature': 0.676762062406568, 'border_count': 141, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.2828976991951257}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:13,567] Trial 97 finished with value: 0.944516944120737 and parameters: {'iterations': 431, 'depth': 14, 'learning_rate': 0.03596250183653654, 'l2_leaf_reg': 2.6049742839678903e-08, 'random_strength': 0.0008507615097739611, 'bagging_temperature': 0.6858858531994815, 'border_count': 43, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.2866478375723365}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:13,860] Trial 98 finished with value: 0.9420281633568404 and parameters: {'iterations': 407, 'depth': 13, 'learning_rate': 0.032590080256233785, 'l2_leaf_reg': 5.3306992270388546e-06, 'random_strength': 0.022674287404467704, 'bagging_temperature': 0.6170819475854629, 'border_count': 166, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.5047854521017533}. Best is trial 24 with value: 0.9479595700629927.\n", - "[I 2025-08-17 19:16:15,792] Trial 99 finished with value: 0.948099087498995 and parameters: {'iterations': 478, 'depth': 12, 'learning_rate': 0.04254101358886379, 'l2_leaf_reg': 1.7277473564532868e-07, 'random_strength': 0.0019440779833289569, 'bagging_temperature': 0.5084286556246295, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 7, 'rsm': 0.37971137763889}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:17,725] Trial 100 finished with value: 0.9421995038264234 and parameters: {'iterations': 447, 'depth': 13, 'learning_rate': 0.054553627666991615, 'l2_leaf_reg': 1.9031563366687202e-07, 'random_strength': 0.001478569010347561, 'bagging_temperature': 0.5020127547283775, 'border_count': 180, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 8, 'rsm': 0.3985919741588475}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:18,099] Trial 101 finished with value: 0.938893699917104 and parameters: {'iterations': 473, 'depth': 12, 'learning_rate': 0.04289147265365806, 'l2_leaf_reg': 7.177530776956312e-08, 'random_strength': 0.005112570354371122, 'bagging_temperature': 0.8041822809136442, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 67, 'rsm': 0.3425524641203796}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:18,829] Trial 102 finished with value: 0.933263873412859 and parameters: {'iterations': 491, 'depth': 12, 'learning_rate': 0.02226381223292443, 'l2_leaf_reg': 9.120516127702251e-07, 'random_strength': 0.0025444221342604914, 'bagging_temperature': 0.564255198899972, 'border_count': 142, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 19, 'rsm': 0.31732954534178587}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:19,365] Trial 103 finished with value: 0.9363490493566118 and parameters: {'iterations': 481, 'depth': 13, 'learning_rate': 0.02483206298542291, 'l2_leaf_reg': 1.5137385022985336e-08, 'random_strength': 0.0007757331181904254, 'bagging_temperature': 0.45248966491294457, 'border_count': 134, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 34, 'rsm': 0.38005525681900953}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:19,840] Trial 104 finished with value: 0.9449682921457203 and parameters: {'iterations': 460, 'depth': 12, 'learning_rate': 0.018505965152376395, 'l2_leaf_reg': 1.5186867963902818e-06, 'random_strength': 0.0015299099277733435, 'bagging_temperature': 0.9604435343858411, 'border_count': 151, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 59, 'rsm': 0.48182633166282013}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:20,085] Trial 105 finished with value: 0.9420419893396765 and parameters: {'iterations': 467, 'depth': 14, 'learning_rate': 0.02999292909768791, 'l2_leaf_reg': 1.0164054698257947e-07, 'random_strength': 0.009267200470185082, 'bagging_temperature': 0.3598497578581198, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.41010965813067535}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:20,351] Trial 106 finished with value: 0.9478823107512284 and parameters: {'iterations': 414, 'depth': 13, 'learning_rate': 0.07309614882931127, 'l2_leaf_reg': 0.0008543057718065979, 'random_strength': 0.0002524560160550367, 'bagging_temperature': 0.4071297784570186, 'border_count': 162, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.266369881554506}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:20,608] Trial 107 finished with value: 0.936463886811552 and parameters: {'iterations': 440, 'depth': 13, 'learning_rate': 0.08190444773381277, 'l2_leaf_reg': 3.214319388206344e-07, 'random_strength': 0.0002612129001674984, 'bagging_temperature': 0.3890984495007036, 'border_count': 147, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 75, 'rsm': 0.270903538495802}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:21,136] Trial 108 finished with value: 0.9308553916078927 and parameters: {'iterations': 416, 'depth': 15, 'learning_rate': 0.10695383481205312, 'l2_leaf_reg': 0.0008919146734425161, 'random_strength': 0.0006207710545904959, 'bagging_temperature': 0.317566864479746, 'border_count': 160, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 70, 'rsm': 0.538778533244966}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:21,430] Trial 109 finished with value: 0.9420281633568404 and parameters: {'iterations': 427, 'depth': 14, 'learning_rate': 0.1469107367152301, 'l2_leaf_reg': 4.444931506830675e-05, 'random_strength': 0.4306633649575429, 'bagging_temperature': 0.535895207806519, 'border_count': 139, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.28942940342239365}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:47,562] Trial 110 finished with value: 0.9141406149187812 and parameters: {'iterations': 393, 'depth': 12, 'learning_rate': 0.0701156386030421, 'l2_leaf_reg': 1.0446575978813497e-08, 'random_strength': 0.003101478071164495, 'bagging_temperature': 0.4225179746298636, 'border_count': 191, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 77, 'rsm': 0.5676355322007246}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:49,102] Trial 111 finished with value: 0.9392980046266818 and parameters: {'iterations': 452, 'depth': 11, 'learning_rate': 0.04157548503684166, 'l2_leaf_reg': 9.034305302437844e-05, 'random_strength': 0.0004057322184259633, 'bagging_temperature': 0.6827176480053725, 'border_count': 167, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 63, 'rsm': 0.3691644950908456}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:50,073] Trial 112 finished with value: 0.9333191418502012 and parameters: {'iterations': 494, 'depth': 12, 'learning_rate': 0.05012391268407289, 'l2_leaf_reg': 2.2291361780007068e-08, 'random_strength': 8.462194507039125e-05, 'bagging_temperature': 0.4730541412136414, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 66, 'rsm': 0.24758489842870557}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:51,388] Trial 113 finished with value: 0.9365108528125179 and parameters: {'iterations': 479, 'depth': 10, 'learning_rate': 0.012897399835445968, 'l2_leaf_reg': 0.0004444637160149302, 'random_strength': 2.21707333469302e-05, 'bagging_temperature': 0.5854775168313623, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 29, 'rsm': 0.6010628227303336}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:52,318] Trial 114 finished with value: 0.9423468716502944 and parameters: {'iterations': 470, 'depth': 13, 'learning_rate': 0.061018518512915516, 'l2_leaf_reg': 0.0015083083238610587, 'random_strength': 0.00015939256236599907, 'bagging_temperature': 0.497044168127894, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.5157982122697622}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:52,675] Trial 115 finished with value: 0.9449308488612835 and parameters: {'iterations': 453, 'depth': 14, 'learning_rate': 0.019576894417447522, 'l2_leaf_reg': 0.00017465568855511566, 'random_strength': 1.0722231591328903e-05, 'bagging_temperature': 0.7402991352316811, 'border_count': 156, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 82, 'rsm': 0.4158043971131127}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:52,876] Trial 116 finished with value: 0.9420281633568404 and parameters: {'iterations': 482, 'depth': 11, 'learning_rate': 0.023401534386045135, 'l2_leaf_reg': 0.0041277449321686505, 'random_strength': 0.16395534032321624, 'bagging_temperature': 0.39074084924312, 'border_count': 229, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 99, 'rsm': 0.16361722425973954}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:53,110] Trial 117 finished with value: 0.9450568845585497 and parameters: {'iterations': 439, 'depth': 12, 'learning_rate': 0.03149277628843053, 'l2_leaf_reg': 0.01123676927285539, 'random_strength': 6.393237174912083e-06, 'bagging_temperature': 0.650201692371258, 'border_count': 138, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.18485433503209892}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:53,368] Trial 118 finished with value: 0.9364356107660455 and parameters: {'iterations': 500, 'depth': 13, 'learning_rate': 0.03673691330874392, 'l2_leaf_reg': 0.2799205983076537, 'random_strength': 0.0016616549946443778, 'bagging_temperature': 1.1434304755513767, 'border_count': 93, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 92, 'rsm': 0.303980336947833}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:53,563] Trial 119 finished with value: 0.9360683747634487 and parameters: {'iterations': 355, 'depth': 10, 'learning_rate': 0.026192218124677005, 'l2_leaf_reg': 5.2505961187717196e-08, 'random_strength': 0.04057701767400652, 'bagging_temperature': 0.28706061899925556, 'border_count': 32, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 42, 'rsm': 0.4499415775570732}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:53,752] Trial 120 finished with value: 0.9420281633568404 and parameters: {'iterations': 373, 'depth': 5, 'learning_rate': 0.04446704544563856, 'l2_leaf_reg': 0.4538460139184795, 'random_strength': 3.1111899899088475e-05, 'bagging_temperature': 0.2425486475025021, 'border_count': 246, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.22838517640724643}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:53,959] Trial 121 finished with value: 0.9394135383169611 and parameters: {'iterations': 460, 'depth': 11, 'learning_rate': 0.017012275631636556, 'l2_leaf_reg': 2.0171376606739177e-07, 'random_strength': 8.792564636872177e-05, 'bagging_temperature': 2.5981546478630135, 'border_count': 122, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.22013559649923678}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:54,218] Trial 122 finished with value: 0.9450568845585497 and parameters: {'iterations': 467, 'depth': 11, 'learning_rate': 0.015246093022030375, 'l2_leaf_reg': 0.19032853338636235, 'random_strength': 1.9249302192365374e-06, 'bagging_temperature': 4.7543569468289455, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.2654905501049236}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:54,412] Trial 123 finished with value: 0.9422759321775974 and parameters: {'iterations': 488, 'depth': 12, 'learning_rate': 0.011621123531896068, 'l2_leaf_reg': 0.037647845056465574, 'random_strength': 5.901004171329165e-05, 'bagging_temperature': 6.224125963475733, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 87, 'rsm': 0.17393984193004308}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:54,708] Trial 124 finished with value: 0.9392165631469979 and parameters: {'iterations': 452, 'depth': 10, 'learning_rate': 0.020963152184374403, 'l2_leaf_reg': 0.0006243147662467919, 'random_strength': 0.0002131427399944794, 'bagging_temperature': 7.743944404779233, 'border_count': 220, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.32484174711862224}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:54,964] Trial 125 finished with value: 0.9366325859360087 and parameters: {'iterations': 476, 'depth': 11, 'learning_rate': 0.010412369273060383, 'l2_leaf_reg': 0.00628453086497708, 'random_strength': 1.0694728932114263e-06, 'bagging_temperature': 0.5377842172748432, 'border_count': 208, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 85, 'rsm': 0.20046815277795216}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:55,238] Trial 126 finished with value: 0.9479394242410895 and parameters: {'iterations': 459, 'depth': 12, 'learning_rate': 0.027921560248912368, 'l2_leaf_reg': 0.0011197201303974583, 'random_strength': 3.7150832167032144e-05, 'bagging_temperature': 0.33772312759685646, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.27829439379604715}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:55,459] Trial 127 finished with value: 0.9478823107512284 and parameters: {'iterations': 416, 'depth': 12, 'learning_rate': 0.02695493912678957, 'l2_leaf_reg': 0.000363754132668095, 'random_strength': 1.6953469751716863e-05, 'bagging_temperature': 0.42078596928585504, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.33967599922122954}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:55,763] Trial 128 finished with value: 0.9420991028295376 and parameters: {'iterations': 414, 'depth': 13, 'learning_rate': 0.030581915215354923, 'l2_leaf_reg': 1.9892774757125386e-05, 'random_strength': 1.9636675912559615e-05, 'bagging_temperature': 0.3441681809788324, 'border_count': 135, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.3535543107245493}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:56,117] Trial 129 finished with value: 0.9393918946301925 and parameters: {'iterations': 432, 'depth': 12, 'learning_rate': 0.028629067859029782, 'l2_leaf_reg': 0.00029759590926787367, 'random_strength': 3.816540308358045e-05, 'bagging_temperature': 0.4304419133130016, 'border_count': 131, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 39, 'rsm': 0.2823066601473922}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:56,471] Trial 130 finished with value: 0.9448319458627505 and parameters: {'iterations': 425, 'depth': 12, 'learning_rate': 0.035334699668356964, 'l2_leaf_reg': 0.002309612414548722, 'random_strength': 9.50603405581896e-06, 'bagging_temperature': 0.1921181189333905, 'border_count': 150, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 55, 'rsm': 0.3421712325642315}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:56,716] Trial 131 finished with value: 0.9365180744718671 and parameters: {'iterations': 463, 'depth': 13, 'learning_rate': 0.2502100961097631, 'l2_leaf_reg': 0.0009007701989759662, 'random_strength': 2.773833098122904e-05, 'bagging_temperature': 0.31330238318056797, 'border_count': 114, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.31829183987372855}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:57,324] Trial 132 finished with value: 0.9136990147276919 and parameters: {'iterations': 442, 'depth': 11, 'learning_rate': 0.024348095854665255, 'l2_leaf_reg': 0.001264909323666646, 'random_strength': 3.150676241429889e-06, 'bagging_temperature': 0.46186652674322926, 'border_count': 143, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 72, 'rsm': 0.8682699354405292}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:57,517] Trial 133 finished with value: 0.9421995038264234 and parameters: {'iterations': 401, 'depth': 12, 'learning_rate': 0.019311103012232354, 'l2_leaf_reg': 0.0019184237342172986, 'random_strength': 0.00010217748102388497, 'bagging_temperature': 0.3695318985236949, 'border_count': 97, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.30183511209079117}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:57,730] Trial 134 finished with value: 0.9423051115089043 and parameters: {'iterations': 489, 'depth': 12, 'learning_rate': 0.02774464488294973, 'l2_leaf_reg': 0.00040945750063480554, 'random_strength': 1.576337834706906e-05, 'bagging_temperature': 0.5123293943299259, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.25543055128232267}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:57,893] Trial 135 finished with value: 0.9391606495664544 and parameters: {'iterations': 475, 'depth': 13, 'learning_rate': 0.02363710203132887, 'l2_leaf_reg': 5.247097796502152e-07, 'random_strength': 1.0426043429706933e-05, 'bagging_temperature': 0.6091999487797312, 'border_count': 127, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 78, 'rsm': 0.10114604580153895}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:58,115] Trial 136 finished with value: 0.9450707105413858 and parameters: {'iterations': 387, 'depth': 11, 'learning_rate': 0.05275588992091221, 'l2_leaf_reg': 8.421747261566226e-05, 'random_strength': 0.000141431813427501, 'bagging_temperature': 0.40818391430649775, 'border_count': 109, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.5305909051010704}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:58,254] Trial 137 finished with value: 0.9422681144736649 and parameters: {'iterations': 388, 'depth': 2, 'learning_rate': 0.054322930763598634, 'l2_leaf_reg': 0.0001949978469938516, 'random_strength': 0.0004333104292700143, 'bagging_temperature': 0.2731806983293307, 'border_count': 103, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 100, 'rsm': 0.498687781787593}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:58,643] Trial 138 finished with value: 0.9390825456894836 and parameters: {'iterations': 347, 'depth': 11, 'learning_rate': 0.040161823283521164, 'l2_leaf_reg': 0.0006602824581046081, 'random_strength': 0.00017097152095899896, 'bagging_temperature': 0.41607380714001674, 'border_count': 136, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 49, 'rsm': 0.5270340614503363}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:58,926] Trial 139 finished with value: 0.9337256816021439 and parameters: {'iterations': 401, 'depth': 14, 'learning_rate': 0.06628587940533412, 'l2_leaf_reg': 1.153850186992474e-05, 'random_strength': 1.0189969346701975e-07, 'bagging_temperature': 0.8727787081175186, 'border_count': 131, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.5621517728185998}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:59,487] Trial 140 finished with value: 0.9309817335506512 and parameters: {'iterations': 447, 'depth': 12, 'learning_rate': 0.04873334111963402, 'l2_leaf_reg': 0.9943938630341599, 'random_strength': 0.016694319781494524, 'bagging_temperature': 0.3512913463453787, 'border_count': 60, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 12, 'rsm': 0.47806253504933655}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:16:59,771] Trial 141 finished with value: 0.9449308488612835 and parameters: {'iterations': 410, 'depth': 11, 'learning_rate': 0.09080696553566514, 'l2_leaf_reg': 9.823038775267924e-05, 'random_strength': 6.939854564405356e-05, 'bagging_temperature': 0.4616531938747425, 'border_count': 108, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.6087092617769291}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:00,004] Trial 142 finished with value: 0.9392165631469979 and parameters: {'iterations': 383, 'depth': 11, 'learning_rate': 0.03210113857890355, 'l2_leaf_reg': 0.0026887421482416993, 'random_strength': 3.765884321811762e-05, 'bagging_temperature': 0.4118834611950506, 'border_count': 115, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 24, 'rsm': 0.13535857801156687}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:00,287] Trial 143 finished with value: 0.9420419893396765 and parameters: {'iterations': 432, 'depth': 10, 'learning_rate': 0.038798992992227554, 'l2_leaf_reg': 0.0034741180567567412, 'random_strength': 0.0002713146202368732, 'bagging_temperature': 1.8012944200478604, 'border_count': 110, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.5400120064708985}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:00,628] Trial 144 finished with value: 0.942245284348707 and parameters: {'iterations': 418, 'depth': 11, 'learning_rate': 0.0791067496320934, 'l2_leaf_reg': 2.0789296632826364, 'random_strength': 0.00012954682210043842, 'bagging_temperature': 0.29682505882415755, 'border_count': 124, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.46616896879851744}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:00,977] Trial 145 finished with value: 0.9307339647298944 and parameters: {'iterations': 456, 'depth': 12, 'learning_rate': 0.057708055393875246, 'l2_leaf_reg': 1.344858568035081e-06, 'random_strength': 4.540543632281483e-06, 'bagging_temperature': 0.5584292910538805, 'border_count': 101, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 90, 'rsm': 0.6415174624180923}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:01,154] Trial 146 finished with value: 0.9391606495664544 and parameters: {'iterations': 483, 'depth': 10, 'learning_rate': 0.044217578258479565, 'l2_leaf_reg': 0.0011889679366554329, 'random_strength': 1.464865467543225, 'bagging_temperature': 0.32672860462852166, 'border_count': 83, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.26647106843219254}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:01,475] Trial 147 finished with value: 0.9364356107660455 and parameters: {'iterations': 468, 'depth': 12, 'learning_rate': 0.021464305942117096, 'l2_leaf_reg': 0.009334993746607368, 'random_strength': 0.000668552265044122, 'bagging_temperature': 8.862006303293871, 'border_count': 116, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.5154318707930476}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:01,820] Trial 148 finished with value: 0.942245284348707 and parameters: {'iterations': 494, 'depth': 13, 'learning_rate': 0.013240135648172328, 'l2_leaf_reg': 9.256222542785185e-08, 'random_strength': 0.004389309226115299, 'bagging_temperature': 0.3810188561669928, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 68, 'rsm': 0.2905578012712258}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:02,182] Trial 149 finished with value: 0.9420419893396765 and parameters: {'iterations': 442, 'depth': 12, 'learning_rate': 0.026276610480490587, 'l2_leaf_reg': 0.018184055160189394, 'random_strength': 0.001160278323404396, 'bagging_temperature': 0.4994469700760825, 'border_count': 129, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 92, 'rsm': 0.5892674146326472}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:02,932] Trial 150 finished with value: 0.9393576247364175 and parameters: {'iterations': 479, 'depth': 11, 'learning_rate': 0.017909665495729164, 'l2_leaf_reg': 3.418791190835952e-08, 'random_strength': 4.9316581417474394e-05, 'bagging_temperature': 0.2581840409523552, 'border_count': 105, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 6, 'rsm': 0.33059365320417256}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:03,120] Trial 151 finished with value: 0.9392165631469979 and parameters: {'iterations': 460, 'depth': 11, 'learning_rate': 0.015844361923020113, 'l2_leaf_reg': 0.06242436487813967, 'random_strength': 2.7294282776467616e-05, 'bagging_temperature': 2.237567853852061, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.15432115118896458}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:03,275] Trial 152 finished with value: 0.9420281633568404 and parameters: {'iterations': 307, 'depth': 10, 'learning_rate': 0.03513004502618466, 'l2_leaf_reg': 0.10677773168166566, 'random_strength': 7.12467611021974e-05, 'bagging_temperature': 3.4000812647715395, 'border_count': 123, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 83, 'rsm': 0.21908078522196517}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:03,556] Trial 153 finished with value: 0.9422897581604335 and parameters: {'iterations': 454, 'depth': 11, 'learning_rate': 0.01736942289114766, 'l2_leaf_reg': 0.6057033139880593, 'random_strength': 1.662852062105787e-05, 'bagging_temperature': 5.1533816618993225, 'border_count': 240, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.2500286572700599}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:03,804] Trial 154 finished with value: 0.9392165631469979 and parameters: {'iterations': 470, 'depth': 11, 'learning_rate': 0.02180369139093789, 'l2_leaf_reg': 5.365532742813126e-06, 'random_strength': 4.764746563966035e-05, 'bagging_temperature': 6.962252063321166, 'border_count': 250, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.24164552701504163}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:04,055] Trial 155 finished with value: 0.9420281633568404 and parameters: {'iterations': 437, 'depth': 12, 'learning_rate': 0.014025048100410055, 'l2_leaf_reg': 0.02942261064762721, 'random_strength': 0.00012661997678511193, 'bagging_temperature': 1.428644549746044, 'border_count': 143, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 61, 'rsm': 0.19733653394586823}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:04,343] Trial 156 finished with value: 0.9424733829640397 and parameters: {'iterations': 424, 'depth': 15, 'learning_rate': 0.027584687851370693, 'l2_leaf_reg': 0.29289799744567774, 'random_strength': 0.00029810253532579494, 'bagging_temperature': 0.5910808047715936, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 89, 'rsm': 0.3649935157963945}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:04,567] Trial 157 finished with value: 0.9422897581604335 and parameters: {'iterations': 500, 'depth': 8, 'learning_rate': 0.00901702182872297, 'l2_leaf_reg': 3.225175618190725e-05, 'random_strength': 5.9851862067132196e-06, 'bagging_temperature': 9.908711348745099, 'border_count': 148, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.2299046581579018}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:04,896] Trial 158 finished with value: 0.9392330734328883 and parameters: {'iterations': 462, 'depth': 13, 'learning_rate': 0.0013935426903720562, 'l2_leaf_reg': 0.14008351382588624, 'random_strength': 2.369260775666672e-05, 'bagging_temperature': 0.4395591771328395, 'border_count': 133, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 74, 'rsm': 0.27863519108727014}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:06,065] Trial 159 finished with value: 0.9301439811851072 and parameters: {'iterations': 155, 'depth': 9, 'learning_rate': 0.019097821061106832, 'l2_leaf_reg': 0.006194130972191863, 'random_strength': 1.4295326838866243e-05, 'bagging_temperature': 0.6814306150232909, 'border_count': 163, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 65, 'rsm': 0.43586584061754363}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:07,160] Trial 160 finished with value: 0.9420218435177732 and parameters: {'iterations': 488, 'depth': 10, 'learning_rate': 0.032756415738802266, 'l2_leaf_reg': 0.0008852235114852314, 'random_strength': 8.600949207782079e-05, 'bagging_temperature': 0.5373270810790087, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 52, 'rsm': 0.4917947838104507}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:07,537] Trial 161 finished with value: 0.9419079718821625 and parameters: {'iterations': 446, 'depth': 4, 'learning_rate': 0.015539514333519456, 'l2_leaf_reg': 4.889776520122877, 'random_strength': 0.0009313366488436875, 'bagging_temperature': 0.3672581246244092, 'border_count': 155, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 2, 'rsm': 0.2673764128336307}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:08,380] Trial 162 finished with value: 0.9448535895495193 and parameters: {'iterations': 475, 'depth': 3, 'learning_rate': 0.021850054135842855, 'l2_leaf_reg': 0.07511660282185649, 'random_strength': 0.0020123581833509357, 'bagging_temperature': 0.344424780392622, 'border_count': 127, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 78, 'rsm': 0.2089112701899995}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:09,247] Trial 163 finished with value: 0.9450568845585497 and parameters: {'iterations': 320, 'depth': 4, 'learning_rate': 0.025276377314971288, 'l2_leaf_reg': 0.1775039781494037, 'random_strength': 5.901525276899961e-07, 'bagging_temperature': 0.47513410689487956, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 45, 'rsm': 0.3056672204395963}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:09,396] Trial 164 finished with value: 0.9420281633568404 and parameters: {'iterations': 451, 'depth': 3, 'learning_rate': 0.017027809049485573, 'l2_leaf_reg': 0.8431126650682025, 'random_strength': 0.006265987027362102, 'bagging_temperature': 0.3287967201175384, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.18023769816221066}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:09,660] Trial 165 finished with value: 0.9391964173250944 and parameters: {'iterations': 441, 'depth': 5, 'learning_rate': 0.019654004388037327, 'l2_leaf_reg': 2.962806671659982, 'random_strength': 0.00046456659205713837, 'bagging_temperature': 0.41793940274356656, 'border_count': 136, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 20, 'rsm': 0.2491760323144459}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:09,841] Trial 166 finished with value: 0.9420281633568404 and parameters: {'iterations': 431, 'depth': 12, 'learning_rate': 0.04825961750253769, 'l2_leaf_reg': 0.3864623653407632, 'random_strength': 0.0002106851591803803, 'bagging_temperature': 0.30726417093872255, 'border_count': 95, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 76, 'rsm': 0.12462026159271422}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:10,749] Trial 167 finished with value: 0.9364292909269782 and parameters: {'iterations': 464, 'depth': 11, 'learning_rate': 0.028930996110599103, 'l2_leaf_reg': 0.04410691026043362, 'random_strength': 0.0011414873923234618, 'bagging_temperature': 0.3772427474271183, 'border_count': 150, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 25, 'rsm': 0.5470029379168437}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:11,025] Trial 168 finished with value: 0.9392165631469979 and parameters: {'iterations': 483, 'depth': 7, 'learning_rate': 0.023530434704186497, 'l2_leaf_reg': 0.00043497423339023495, 'random_strength': 3.700167074678586e-05, 'bagging_temperature': 0.6287303886622022, 'border_count': 178, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 82, 'rsm': 0.2872040142291833}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:11,352] Trial 169 finished with value: 0.9391606495664544 and parameters: {'iterations': 419, 'depth': 11, 'learning_rate': 0.011066677702838626, 'l2_leaf_reg': 3.3218560135089747e-07, 'random_strength': 6.273259312642815e-05, 'bagging_temperature': 0.47382001617043684, 'border_count': 90, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 14, 'rsm': 0.1503567953926859}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:11,502] Trial 170 finished with value: 0.9420281633568404 and parameters: {'iterations': 410, 'depth': 4, 'learning_rate': 0.06752711692568371, 'l2_leaf_reg': 0.001710704283225401, 'random_strength': 7.762246146156258e-06, 'bagging_temperature': 7.677579394294883, 'border_count': 106, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.22951185589278955}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:11,668] Trial 171 finished with value: 0.939247210975888 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.02000585732933726, 'l2_leaf_reg': 0.0006763625137768598, 'random_strength': 0.0005407013316711388, 'bagging_temperature': 0.5340715524087578, 'border_count': 101, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.16311940628182714}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:11,837] Trial 172 finished with value: 0.9420281633568404 and parameters: {'iterations': 492, 'depth': 5, 'learning_rate': 0.014896680959692137, 'l2_leaf_reg': 1.4385889711686615, 'random_strength': 0.0007178660770454293, 'bagging_temperature': 0.7563960208234407, 'border_count': 111, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 86, 'rsm': 0.17243296476590866}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:12,000] Trial 173 finished with value: 0.9450568845585497 and parameters: {'iterations': 473, 'depth': 5, 'learning_rate': 0.023027426925292, 'l2_leaf_reg': 0.0002781682518945414, 'random_strength': 0.00010782305847558164, 'bagging_temperature': 0.5867396501064782, 'border_count': 99, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 84, 'rsm': 0.19470730255701207}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:12,235] Trial 174 finished with value: 0.939377770558321 and parameters: {'iterations': 482, 'depth': 4, 'learning_rate': 0.03241964888238338, 'l2_leaf_reg': 0.0003457154290776943, 'random_strength': 0.00044451681264570474, 'bagging_temperature': 0.4432670512593227, 'border_count': 233, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 80, 'rsm': 0.26332909539982013}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:12,533] Trial 175 finished with value: 0.9394832914849566 and parameters: {'iterations': 457, 'depth': 13, 'learning_rate': 0.04045814491944505, 'l2_leaf_reg': 0.0001402936281707434, 'random_strength': 0.0001840161471214937, 'bagging_temperature': 0.5079765193842785, 'border_count': 213, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 87, 'rsm': 0.3167030107845214}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:12,760] Trial 176 finished with value: 0.9420281633568404 and parameters: {'iterations': 493, 'depth': 4, 'learning_rate': 0.027519881479168753, 'l2_leaf_reg': 0.004053512628934247, 'random_strength': 0.0003219786489434715, 'bagging_temperature': 0.41135083844257087, 'border_count': 185, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 92, 'rsm': 0.34090137490760997}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:13,115] Trial 177 finished with value: 0.9478701466895731 and parameters: {'iterations': 294, 'depth': 14, 'learning_rate': 0.017432667951942236, 'l2_leaf_reg': 8.069010518000647e-05, 'random_strength': 0.10401852426690426, 'bagging_temperature': 0.22484682170681464, 'border_count': 203, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 98, 'rsm': 0.5766975974859562}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:13,395] Trial 178 finished with value: 0.9423087176776352 and parameters: {'iterations': 265, 'depth': 14, 'learning_rate': 0.01247518250258224, 'l2_leaf_reg': 0.0002203658912485584, 'random_strength': 0.1334227737202125, 'bagging_temperature': 0.2670035665869987, 'border_count': 196, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.5318296390483455}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:13,644] Trial 179 finished with value: 0.9448535895495193 and parameters: {'iterations': 238, 'depth': 14, 'learning_rate': 0.01807673012308473, 'l2_leaf_reg': 0.01399085651991093, 'random_strength': 0.2960932676404893, 'bagging_temperature': 0.15351918050488025, 'border_count': 255, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 96, 'rsm': 0.5114009411786454}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:13,998] Trial 180 finished with value: 0.9449107030393801 and parameters: {'iterations': 450, 'depth': 14, 'learning_rate': 0.03589837606023441, 'l2_leaf_reg': 6.662649961466868e-05, 'random_strength': 0.07909578018195974, 'bagging_temperature': 0.23722827797048798, 'border_count': 132, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.2793912618414582}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:14,157] Trial 181 finished with value: 0.9422031967509996 and parameters: {'iterations': 282, 'depth': 3, 'learning_rate': 0.020907669083619945, 'l2_leaf_reg': 4.0417023367134544e-05, 'random_strength': 0.0029292950598705124, 'bagging_temperature': 0.2048019984702627, 'border_count': 114, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 98, 'rsm': 0.5726568945580828}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:14,532] Trial 182 finished with value: 0.9308692175907287 and parameters: {'iterations': 300, 'depth': 16, 'learning_rate': 0.016977587931415225, 'l2_leaf_reg': 6.428861894888382e-05, 'random_strength': 4.481525163941594e-05, 'bagging_temperature': 0.2915045702805398, 'border_count': 202, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 94, 'rsm': 0.5886491339618192}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:14,761] Trial 183 finished with value: 0.9394769716458893 and parameters: {'iterations': 221, 'depth': 12, 'learning_rate': 0.024351404002375798, 'l2_leaf_reg': 0.000571971133855846, 'random_strength': 2.4460781047220314e-05, 'bagging_temperature': 0.22238886441296601, 'border_count': 172, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 100, 'rsm': 0.5577041652720683}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:15,345] Trial 184 finished with value: 0.9478606670644598 and parameters: {'iterations': 374, 'depth': 10, 'learning_rate': 0.018862089757160656, 'l2_leaf_reg': 0.0002711773955536017, 'random_strength': 0.00013899680340439353, 'bagging_temperature': 4.376392538372629, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 10, 'rsm': 0.21282910430945437}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:15,933] Trial 185 finished with value: 0.9422251385268036 and parameters: {'iterations': 373, 'depth': 10, 'learning_rate': 0.01341908033642766, 'l2_leaf_reg': 1.3301485751827285e-07, 'random_strength': 8.258702096105676e-05, 'bagging_temperature': 6.313550576053137, 'border_count': 125, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 8, 'rsm': 0.21582168224439763}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:16,955] Trial 186 finished with value: 0.9366461056733522 and parameters: {'iterations': 354, 'depth': 11, 'learning_rate': 0.016015514757403242, 'l2_leaf_reg': 0.0012157604267309754, 'random_strength': 0.00014286883311715454, 'bagging_temperature': 3.8355646079201944, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 4, 'rsm': 0.24455713560531547}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:18,240] Trial 187 finished with value: 0.9393714507192537 and parameters: {'iterations': 387, 'depth': 9, 'learning_rate': 0.029773522710607077, 'l2_leaf_reg': 0.18964502202298492, 'random_strength': 0.05665749832122518, 'bagging_temperature': 4.316804556211732, 'border_count': 224, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 5, 'rsm': 0.29112694915279064}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:19,109] Trial 188 finished with value: 0.9365246787953542 and parameters: {'iterations': 328, 'depth': 10, 'learning_rate': 0.019103470294199343, 'l2_leaf_reg': 6.562015740609845, 'random_strength': 0.030892780955495254, 'bagging_temperature': 5.561691546696606, 'border_count': 129, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 10, 'rsm': 0.6181631034200274}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:20,111] Trial 189 finished with value: 0.9364154649441421 and parameters: {'iterations': 363, 'depth': 12, 'learning_rate': 0.014354312995037964, 'l2_leaf_reg': 0.0881351634444277, 'random_strength': 1.973507344724729e-06, 'bagging_temperature': 8.141642491918113, 'border_count': 137, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 16, 'rsm': 0.19449893094423057}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:49,051] Trial 190 finished with value: 0.9326620320519092 and parameters: {'iterations': 394, 'depth': 13, 'learning_rate': 0.02538912391774518, 'l2_leaf_reg': 0.0024456588938525075, 'random_strength': 0.09893594885717653, 'bagging_temperature': 2.6586561536924234, 'border_count': 119, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 97, 'rsm': 0.4961944560276764}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:50,393] Trial 191 finished with value: 0.9364356107660455 and parameters: {'iterations': 377, 'depth': 15, 'learning_rate': 0.02160748607378081, 'l2_leaf_reg': 0.00018784167765087707, 'random_strength': 5.661101716609462e-05, 'bagging_temperature': 0.5520159277072044, 'border_count': 105, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 33, 'rsm': 0.13638530175267316}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:51,336] Trial 192 finished with value: 0.9365766723554652 and parameters: {'iterations': 345, 'depth': 11, 'learning_rate': 0.018153545563738348, 'l2_leaf_reg': 0.0002689381199903756, 'random_strength': 0.0013202072873539827, 'bagging_temperature': 3.05875393809237, 'border_count': 108, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 47, 'rsm': 0.1833083713837859}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:52,234] Trial 193 finished with value: 0.9422759321775974 and parameters: {'iterations': 472, 'depth': 11, 'learning_rate': 0.01967261015798756, 'l2_leaf_reg': 0.00010269003059595126, 'random_strength': 0.0003224919649464639, 'bagging_temperature': 4.7403514956391515, 'border_count': 114, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.22203325266748072}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:52,590] Trial 194 finished with value: 0.9450707105413858 and parameters: {'iterations': 479, 'depth': 12, 'learning_rate': 0.022953910052071345, 'l2_leaf_reg': 0.00033355714664964474, 'random_strength': 0.00021059453778553297, 'bagging_temperature': 0.3911695421583786, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.53058333271746}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:52,915] Trial 195 finished with value: 0.9479595700629927 and parameters: {'iterations': 468, 'depth': 12, 'learning_rate': 0.027646391674950158, 'l2_leaf_reg': 0.0008940375907121934, 'random_strength': 0.00017370575325460964, 'bagging_temperature': 0.17637761154801543, 'border_count': 123, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 92, 'rsm': 0.5383588788987733}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:53,243] Trial 196 finished with value: 0.9448749352807401 and parameters: {'iterations': 466, 'depth': 12, 'learning_rate': 0.031699768142828835, 'l2_leaf_reg': 0.0010108484321680307, 'random_strength': 0.00015777611403595265, 'bagging_temperature': 0.14876062009712754, 'border_count': 126, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.5254795998656782}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:53,584] Trial 197 finished with value: 0.9334006901311248 and parameters: {'iterations': 482, 'depth': 12, 'learning_rate': 0.026842474376006505, 'l2_leaf_reg': 0.0006848580407660518, 'random_strength': 0.00010498978622202728, 'bagging_temperature': 0.18830195664870608, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 94, 'rsm': 0.5497198397999028}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:53,820] Trial 198 finished with value: 0.9420419893396765 and parameters: {'iterations': 295, 'depth': 12, 'learning_rate': 0.03677738161683119, 'l2_leaf_reg': 0.00036343825894797515, 'random_strength': 0.0002479113992623705, 'bagging_temperature': 0.14005757368990798, 'border_count': 122, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 89, 'rsm': 0.5391037144265599}. Best is trial 99 with value: 0.948099087498995.\n", - "[I 2025-08-17 19:17:54,203] Trial 199 finished with value: 0.9450707105413858 and parameters: {'iterations': 460, 'depth': 12, 'learning_rate': 0.04545859371569691, 'l2_leaf_reg': 0.0016986307026388967, 'random_strength': 3.772429639477264e-05, 'bagging_temperature': 0.1322329379931608, 'border_count': 128, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 97, 'rsm': 0.5717542930999647}. Best is trial 99 with value: 0.948099087498995.\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**LightGBM results:**" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best trial:\n", - "F1 Score: 0.948099\n", - "Parameters:\n", - "iterations: 478\n", - "depth: 12\n", - "learning_rate: 0.04254101358886379\n", - "l2_leaf_reg: 1.7277473564532868e-07\n", - "random_strength: 0.0019440779833289569\n", - "bagging_temperature: 0.5084286556246295\n", - "border_count: 140\n", - "grow_policy: Depthwise\n", - "min_data_in_leaf: 7\n", - "rsm: 0.37971137763889\n" - ] - } - ], - "source": [ - "from catboost import CatBoostClassifier\n", - "\n", - "\n", - "def objective(trial):\n", - " params = {\n", - " \"iterations\": trial.suggest_int(\"iterations\", 50, 500),\n", - " \"depth\": trial.suggest_int(\"depth\", 1, 16),\n", - " \"learning_rate\": trial.suggest_float(\"learning_rate\", 1e-3, 0.5, log=True),\n", - " \"l2_leaf_reg\": trial.suggest_float(\"l2_leaf_reg\", 1e-8, 10.0, log=True),\n", - " \"random_strength\": trial.suggest_float(\"random_strength\", 1e-8, 10.0, log=True),\n", - " \"bagging_temperature\": trial.suggest_float(\n", - " \"bagging_temperature\", 0.1, 10.0, log=True\n", - " ),\n", - " \"border_count\": trial.suggest_int(\"border_count\", 32, 255),\n", - " \"grow_policy\": trial.suggest_categorical(\n", - " \"grow_policy\", [\"SymmetricTree\", \"Depthwise\", \"Lossguide\"]\n", - " ),\n", - " \"min_data_in_leaf\": trial.suggest_int(\"min_data_in_leaf\", 1, 100),\n", - " \"rsm\": trial.suggest_float(\"rsm\", 0.1, 1.0),\n", - " \"loss_function\": \"Logloss\",\n", - " \"eval_metric\": \"F1\",\n", - " \"cat_features\": categorical_cols,\n", - " \"verbose\": 0,\n", - " }\n", - "\n", - " model = CatBoostClassifier(**params)\n", - "\n", - " scores = cross_val_score(\n", - " estimator=model,\n", - " X=X,\n", - " y=y,\n", - " scoring=\"f1_weighted\",\n", - " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", - " n_jobs=-1,\n", - " )\n", - "\n", - " return scores.mean()\n", - "\n", - "\n", - "study = optuna.create_study(direction=\"maximize\")\n", - "study.optimize(objective, n_trials=200)\n", - "\n", - "best_trial = study.best_trial\n", - "\n", - "print(\"Best trial:\")\n", - "print(f\"F1 Score: {best_trial.value:.6f}\")\n", - "print(\"Parameters:\")\n", - "for k, v in best_trial.params.items():\n", - " print(f\"{k}: {v}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-18 21:38:31,112] A new study created in memory with name: no-name-a2c71fbc-43fe-4d55-a82d-10f7362f12f0\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[LightGBM] [Fatal] Do not support special JSON characters in feature name.\n", + "[W 2025-08-18 21:38:31,823] Trial 0 failed with parameters: {'boosting_type': 'gbdt', 'num_leaves': 231, 'learning_rate': 0.004729326807185178, 'n_estimators': 180, 'max_depth': 15, 'min_child_samples': 62, 'subsample': 0.95535818357979, 'colsample_bytree': 0.7438374709143218, 'reg_alpha': 1.0331517436951706e-05, 'reg_lambda': 1.2172287308521004e-05, 'min_split_gain': 4.144384519107149e-06, 'cat_smooth': 47, 'cat_l2': 2.5374071883620803e-07} because of the following error: ValueError('\\nAll the 10 fits failed.\\nIt is very likely that your model is misconfigured.\\nYou can try to debug the error by setting error_score=\\'raise\\'.\\n\\nBelow are more details about the failures:\\n--------------------------------------------------------------------------------\\n10 fits failed with the following error:\\nTraceback (most recent call last):\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\\n estimator.fit(X_train, y_train, **fit_params)\\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\\n super().fit(\\n ~~~~~~~~~~~^\\n X,\\n ^^\\n ...<12 lines>...\\n init_model=init_model,\\n ^^^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\\n self._Booster = train(\\n ~~~~~^\\n params=params,\\n ^^^^^^^^^^^^^^\\n ...<6 lines>...\\n callbacks=callbacks,\\n ^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\\n booster = Booster(params=params, train_set=train_set)\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\\n train_set.construct()\\n ~~~~~~~~~~~~~~~~~~~^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\\n self._lazy_init(\\n ~~~~~~~~~~~~~~~^\\n data=self.data,\\n ^^^^^^^^^^^^^^^\\n ...<9 lines>...\\n position=self.position,\\n ^^^^^^^^^^^^^^^^^^^^^^^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\\n return self.set_feature_name(feature_name)\\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\\n _safe_call(\\n ~~~~~~~~~~^\\n _LIB.LGBM_DatasetSetFeatureNames(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n ...<3 lines>...\\n )\\n ^\\n )\\n ^\\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\\n').\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py\", line 201, in _run_trial\n", + " value_or_values = func(trial)\n", + " File \"/var/folders/dj/6m_rn6_56pvb0zb7k0t6bz4r0000gn/T/ipykernel_47070/4223881388.py\", line 28, in objective\n", + " scores = cross_val_score(\n", + " estimator=model,\n", + " ...<4 lines>...\n", + " n_jobs=-1,\n", + " )\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py\", line 216, in wrapper\n", + " return func(*args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 684, in cross_val_score\n", + " cv_results = cross_validate(\n", + " estimator=estimator,\n", + " ...<9 lines>...\n", + " error_score=error_score,\n", + " )\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py\", line 216, in wrapper\n", + " return func(*args, **kwargs)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 431, in cross_validate\n", + " _warn_or_raise_about_fit_failures(results, error_score)\n", + " ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 517, in _warn_or_raise_about_fit_failures\n", + " raise ValueError(all_fits_failed_message)\n", + "ValueError: \n", + "All the 10 fits failed.\n", + "It is very likely that your model is misconfigured.\n", + "You can try to debug the error by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n", + " super().fit(\n", + " ~~~~~~~~~~~^\n", + " X,\n", + " ^^\n", + " ...<12 lines>...\n", + " init_model=init_model,\n", + " ^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n", + " self._Booster = train(\n", + " ~~~~~^\n", + " params=params,\n", + " ^^^^^^^^^^^^^^\n", + " ...<6 lines>...\n", + " callbacks=callbacks,\n", + " ^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n", + " booster = Booster(params=params, train_set=train_set)\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n", + " train_set.construct()\n", + " ~~~~~~~~~~~~~~~~~~~^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n", + " self._lazy_init(\n", + " ~~~~~~~~~~~~~~~^\n", + " data=self.data,\n", + " ^^^^^^^^^^^^^^^\n", + " ...<9 lines>...\n", + " position=self.position,\n", + " ^^^^^^^^^^^^^^^^^^^^^^^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n", + " return self.set_feature_name(feature_name)\n", + " ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n", + " _safe_call(\n", + " ~~~~~~~~~~^\n", + " _LIB.LGBM_DatasetSetFeatureNames(\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " ...<3 lines>...\n", + " )\n", + " ^\n", + " )\n", + " ^\n", + " File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n", + " raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\n", + "lightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n", + "\n", + "[W 2025-08-18 21:38:31,824] Trial 0 failed with value None.\n" + ] + }, + { + "ename": "ValueError", + "evalue": "\nAll the 10 fits failed.\nIt is very likely that your model is misconfigured.\nYou can try to debug the error by setting error_score='raise'.\n\nBelow are more details about the failures:\n--------------------------------------------------------------------------------\n10 fits failed with the following error:\nTraceback (most recent call last):\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n estimator.fit(X_train, y_train, **fit_params)\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n super().fit(\n ~~~~~~~~~~~^\n X,\n ^^\n ...<12 lines>...\n init_model=init_model,\n ^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n self._Booster = train(\n ~~~~~^\n params=params,\n ^^^^^^^^^^^^^^\n ...<6 lines>...\n callbacks=callbacks,\n ^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n booster = Booster(params=params, train_set=train_set)\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n train_set.construct()\n ~~~~~~~~~~~~~~~~~~~^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n self._lazy_init(\n ~~~~~~~~~~~~~~~^\n data=self.data,\n ^^^^^^^^^^^^^^^\n ...<9 lines>...\n position=self.position,\n ^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n return self.set_feature_name(feature_name)\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n _safe_call(\n ~~~~~~~~~~^\n _LIB.LGBM_DatasetSetFeatureNames(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<3 lines>...\n )\n ^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mValueError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 41\u001b[39m\n\u001b[32m 37\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores.mean()\n\u001b[32m 40\u001b[39m study = optuna.create_study(direction=\u001b[33m\"\u001b[39m\u001b[33mmaximize\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m41\u001b[39m \u001b[43mstudy\u001b[49m\u001b[43m.\u001b[49m\u001b[43moptimize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobjective\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m200\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m best_trial = study.best_trial\n\u001b[32m 45\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mBest trial:\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/study.py:489\u001b[39m, in \u001b[36mStudy.optimize\u001b[39m\u001b[34m(self, func, n_trials, timeout, n_jobs, catch, callbacks, gc_after_trial, show_progress_bar)\u001b[39m\n\u001b[32m 387\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34moptimize\u001b[39m(\n\u001b[32m 388\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m 389\u001b[39m func: ObjectiveFuncType,\n\u001b[32m (...)\u001b[39m\u001b[32m 396\u001b[39m show_progress_bar: \u001b[38;5;28mbool\u001b[39m = \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[32m 397\u001b[39m ) -> \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m 398\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Optimize an objective function.\u001b[39;00m\n\u001b[32m 399\u001b[39m \n\u001b[32m 400\u001b[39m \u001b[33;03m Optimization is done by choosing a suitable set of hyperparameter values from a given\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 487\u001b[39m \u001b[33;03m If nested invocation of this method occurs.\u001b[39;00m\n\u001b[32m 488\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m489\u001b[39m \u001b[43m_optimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 490\u001b[39m \u001b[43m \u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 491\u001b[39m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 492\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 493\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 494\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 495\u001b[39m \u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mIterable\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 496\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 497\u001b[39m \u001b[43m \u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 498\u001b[39m \u001b[43m \u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mshow_progress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 499\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:64\u001b[39m, in \u001b[36m_optimize\u001b[39m\u001b[34m(study, func, n_trials, timeout, n_jobs, catch, callbacks, gc_after_trial, show_progress_bar)\u001b[39m\n\u001b[32m 62\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 63\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m n_jobs == \u001b[32m1\u001b[39m:\n\u001b[32m---> \u001b[39m\u001b[32m64\u001b[39m \u001b[43m_optimize_sequential\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 65\u001b[39m \u001b[43m \u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 66\u001b[39m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 67\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_trials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 68\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 69\u001b[39m \u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 70\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 71\u001b[39m \u001b[43m \u001b[49m\u001b[43mgc_after_trial\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 72\u001b[39m \u001b[43m \u001b[49m\u001b[43mreseed_sampler_rng\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 73\u001b[39m \u001b[43m \u001b[49m\u001b[43mtime_start\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 74\u001b[39m \u001b[43m \u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 75\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 76\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 77\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m n_jobs == -\u001b[32m1\u001b[39m:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:161\u001b[39m, in \u001b[36m_optimize_sequential\u001b[39m\u001b[34m(study, func, n_trials, timeout, catch, callbacks, gc_after_trial, reseed_sampler_rng, time_start, progress_bar)\u001b[39m\n\u001b[32m 158\u001b[39m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[32m 160\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m161\u001b[39m frozen_trial = \u001b[43m_run_trial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstudy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 162\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 163\u001b[39m \u001b[38;5;66;03m# The following line mitigates memory problems that can be occurred in some\u001b[39;00m\n\u001b[32m 164\u001b[39m \u001b[38;5;66;03m# environments (e.g., services that use computing containers such as GitHub Actions).\u001b[39;00m\n\u001b[32m 165\u001b[39m \u001b[38;5;66;03m# Please refer to the following PR for further details:\u001b[39;00m\n\u001b[32m 166\u001b[39m \u001b[38;5;66;03m# https://github.com/optuna/optuna/pull/325.\u001b[39;00m\n\u001b[32m 167\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m gc_after_trial:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:253\u001b[39m, in \u001b[36m_run_trial\u001b[39m\u001b[34m(study, func, catch)\u001b[39m\n\u001b[32m 246\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[33m\"\u001b[39m\u001b[33mShould not reach.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 248\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[32m 249\u001b[39m frozen_trial.state == TrialState.FAIL\n\u001b[32m 250\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m func_err \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 251\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(func_err, catch)\n\u001b[32m 252\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m253\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m func_err\n\u001b[32m 254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m frozen_trial\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/optuna/study/_optimize.py:201\u001b[39m, in \u001b[36m_run_trial\u001b[39m\u001b[34m(study, func, catch)\u001b[39m\n\u001b[32m 199\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m get_heartbeat_thread(trial._trial_id, study._storage):\n\u001b[32m 200\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m201\u001b[39m value_or_values = \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrial\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 202\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m exceptions.TrialPruned \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 203\u001b[39m \u001b[38;5;66;03m# TODO(mamu): Handle multi-objective cases.\u001b[39;00m\n\u001b[32m 204\u001b[39m state = TrialState.PRUNED\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 28\u001b[39m, in \u001b[36mobjective\u001b[39m\u001b[34m(trial)\u001b[39m\n\u001b[32m 5\u001b[39m params = {\n\u001b[32m 6\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mobjective\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mbinary\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 7\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmetric\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mbinary_logloss\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 23\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mverbosity\u001b[39m\u001b[33m\"\u001b[39m: -\u001b[32m1\u001b[39m,\n\u001b[32m 24\u001b[39m }\n\u001b[32m 26\u001b[39m model = lgb.LGBMClassifier(**params)\n\u001b[32m---> \u001b[39m\u001b[32m28\u001b[39m scores = \u001b[43mcross_val_score\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 29\u001b[39m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 30\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m=\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 31\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m=\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 32\u001b[39m \u001b[43m \u001b[49m\u001b[43mscoring\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mf1_weighted\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 33\u001b[39m \u001b[43m \u001b[49m\u001b[43mcv\u001b[49m\u001b[43m=\u001b[49m\u001b[43mStratifiedKFold\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_splits\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m10\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshuffle\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrandom_state\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m42\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 34\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 35\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 37\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m scores.mean()\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py:216\u001b[39m, in \u001b[36mvalidate_params..decorator..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 210\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 211\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 212\u001b[39m skip_parameter_validation=(\n\u001b[32m 213\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 214\u001b[39m )\n\u001b[32m 215\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m216\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 218\u001b[39m \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[32m 219\u001b[39m \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[32m 220\u001b[39m \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[32m 221\u001b[39m \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[32m 222\u001b[39m msg = re.sub(\n\u001b[32m 223\u001b[39m \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[33m\\\u001b[39m\u001b[33mw+ must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 224\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc.\u001b[34m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 225\u001b[39m \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[32m 226\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:684\u001b[39m, in \u001b[36mcross_val_score\u001b[39m\u001b[34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, params, pre_dispatch, error_score)\u001b[39m\n\u001b[32m 681\u001b[39m \u001b[38;5;66;03m# To ensure multimetric format is not supported\u001b[39;00m\n\u001b[32m 682\u001b[39m scorer = check_scoring(estimator, scoring=scoring)\n\u001b[32m--> \u001b[39m\u001b[32m684\u001b[39m cv_results = \u001b[43mcross_validate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 685\u001b[39m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m=\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 686\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m=\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 687\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m=\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 688\u001b[39m \u001b[43m \u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 689\u001b[39m \u001b[43m \u001b[49m\u001b[43mscoring\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mscore\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mscorer\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 690\u001b[39m \u001b[43m \u001b[49m\u001b[43mcv\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 691\u001b[39m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 692\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 693\u001b[39m \u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[43m=\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 694\u001b[39m \u001b[43m \u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpre_dispatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 695\u001b[39m \u001b[43m \u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m=\u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 696\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 697\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cv_results[\u001b[33m\"\u001b[39m\u001b[33mtest_score\u001b[39m\u001b[33m\"\u001b[39m]\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/utils/_param_validation.py:216\u001b[39m, in \u001b[36mvalidate_params..decorator..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 210\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 211\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 212\u001b[39m skip_parameter_validation=(\n\u001b[32m 213\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 214\u001b[39m )\n\u001b[32m 215\u001b[39m ):\n\u001b[32m--> \u001b[39m\u001b[32m216\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m InvalidParameterError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 218\u001b[39m \u001b[38;5;66;03m# When the function is just a wrapper around an estimator, we allow\u001b[39;00m\n\u001b[32m 219\u001b[39m \u001b[38;5;66;03m# the function to delegate validation to the estimator, but we replace\u001b[39;00m\n\u001b[32m 220\u001b[39m \u001b[38;5;66;03m# the name of the estimator by the name of the function in the error\u001b[39;00m\n\u001b[32m 221\u001b[39m \u001b[38;5;66;03m# message to avoid confusion.\u001b[39;00m\n\u001b[32m 222\u001b[39m msg = re.sub(\n\u001b[32m 223\u001b[39m \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[33m\\\u001b[39m\u001b[33mw+ must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 224\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mparameter of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunc.\u001b[34m__qualname__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m must be\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 225\u001b[39m \u001b[38;5;28mstr\u001b[39m(e),\n\u001b[32m 226\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:431\u001b[39m, in \u001b[36mcross_validate\u001b[39m\u001b[34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, params, pre_dispatch, return_train_score, return_estimator, return_indices, error_score)\u001b[39m\n\u001b[32m 410\u001b[39m parallel = Parallel(n_jobs=n_jobs, verbose=verbose, pre_dispatch=pre_dispatch)\n\u001b[32m 411\u001b[39m results = parallel(\n\u001b[32m 412\u001b[39m delayed(_fit_and_score)(\n\u001b[32m 413\u001b[39m clone(estimator),\n\u001b[32m (...)\u001b[39m\u001b[32m 428\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m train, test \u001b[38;5;129;01min\u001b[39;00m indices\n\u001b[32m 429\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m431\u001b[39m \u001b[43m_warn_or_raise_about_fit_failures\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresults\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merror_score\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 433\u001b[39m \u001b[38;5;66;03m# For callable scoring, the return type is only know after calling. If the\u001b[39;00m\n\u001b[32m 434\u001b[39m \u001b[38;5;66;03m# return type is a dictionary, the error scores can now be inserted with\u001b[39;00m\n\u001b[32m 435\u001b[39m \u001b[38;5;66;03m# the correct key.\u001b[39;00m\n\u001b[32m 436\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcallable\u001b[39m(scoring):\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py:517\u001b[39m, in \u001b[36m_warn_or_raise_about_fit_failures\u001b[39m\u001b[34m(results, error_score)\u001b[39m\n\u001b[32m 510\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m num_failed_fits == num_fits:\n\u001b[32m 511\u001b[39m all_fits_failed_message = (\n\u001b[32m 512\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mAll the \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m fits failed.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 513\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mIt is very likely that your model is misconfigured.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 514\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mYou can try to debug the error by setting error_score=\u001b[39m\u001b[33m'\u001b[39m\u001b[33mraise\u001b[39m\u001b[33m'\u001b[39m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 515\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mBelow are more details about the failures:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mfit_errors_summary\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 516\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m517\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(all_fits_failed_message)\n\u001b[32m 519\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 520\u001b[39m some_fits_failed_message = (\n\u001b[32m 521\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mnum_failed_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m fits failed out of a total of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_fits\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 522\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mThe score on these train-test partitions for these parameters\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m (...)\u001b[39m\u001b[32m 526\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mBelow are more details about the failures:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mfit_errors_summary\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 527\u001b[39m )\n", + "\u001b[31mValueError\u001b[39m: \nAll the 10 fits failed.\nIt is very likely that your model is misconfigured.\nYou can try to debug the error by setting error_score='raise'.\n\nBelow are more details about the failures:\n--------------------------------------------------------------------------------\n10 fits failed with the following error:\nTraceback (most recent call last):\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/sklearn/model_selection/_validation.py\", line 866, in _fit_and_score\n estimator.fit(X_train, y_train, **fit_params)\n ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1560, in fit\n super().fit(\n ~~~~~~~~~~~^\n X,\n ^^\n ...<12 lines>...\n init_model=init_model,\n ^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/sklearn.py\", line 1049, in fit\n self._Booster = train(\n ~~~~~^\n params=params,\n ^^^^^^^^^^^^^^\n ...<6 lines>...\n callbacks=callbacks,\n ^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/engine.py\", line 297, in train\n booster = Booster(params=params, train_set=train_set)\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3656, in __init__\n train_set.construct()\n ~~~~~~~~~~~~~~~~~~~^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2590, in construct\n self._lazy_init(\n ~~~~~~~~~~~~~~~^\n data=self.data,\n ^^^^^^^^^^^^^^^\n ...<9 lines>...\n position=self.position,\n ^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 2227, in _lazy_init\n return self.set_feature_name(feature_name)\n ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 3046, in set_feature_name\n _safe_call(\n ~~~~~~~~~~^\n _LIB.LGBM_DatasetSetFeatureNames(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<3 lines>...\n )\n ^\n )\n ^\n File \"/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/lightgbm/basic.py\", line 313, in _safe_call\n raise LightGBMError(_LIB.LGBM_GetLastError().decode(\"utf-8\"))\nlightgbm.basic.LightGBMError: Do not support special JSON characters in feature name.\n" + ] + } + ], + "source": [ + "import lightgbm as lgb\n", + "\n", + "\n", + "def objective(trial):\n", + " params = {\n", + " \"objective\": \"binary\",\n", + " \"metric\": \"binary_logloss\",\n", + " \"boosting_type\": trial.suggest_categorical(\n", + " \"boosting_type\", [\"gbdt\", \"dart\", \"goss\"]\n", + " ),\n", + " \"num_leaves\": trial.suggest_int(\"num_leaves\", 2, 256),\n", + " \"learning_rate\": trial.suggest_float(\"learning_rate\", 1e-3, 0.1, log=True),\n", + " \"n_estimators\": trial.suggest_int(\"n_estimators\", 20, 1000),\n", + " \"max_depth\": trial.suggest_int(\"max_depth\", 1, 20),\n", + " \"min_child_samples\": trial.suggest_int(\"min_child_samples\", 1, 100),\n", + " \"subsample\": trial.suggest_float(\"subsample\", 0.5, 1.0),\n", + " \"colsample_bytree\": trial.suggest_float(\"colsample_bytree\", 0.5, 1.0),\n", + " \"reg_alpha\": trial.suggest_float(\"reg_alpha\", 1e-8, 10.0, log=True),\n", + " \"reg_lambda\": trial.suggest_float(\"reg_lambda\", 1e-8, 10.0, log=True),\n", + " \"min_split_gain\": trial.suggest_float(\"min_split_gain\", 1e-8, 1.0, log=True),\n", + " \"cat_smooth\": trial.suggest_int(\"cat_smooth\", 1, 100),\n", + " \"cat_l2\": trial.suggest_float(\"cat_l2\", 1e-8, 10.0, log=True),\n", + " \"verbosity\": -1,\n", + " }\n", + "\n", + " model = lgb.LGBMClassifier(**params)\n", + "\n", + " scores = cross_val_score(\n", + " estimator=model,\n", + " X=X,\n", + " y=y,\n", + " scoring=\"f1_weighted\",\n", + " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", + " n_jobs=-1,\n", + " )\n", + "\n", + " return scores.mean()\n", + "\n", + "\n", + "study = optuna.create_study(direction=\"maximize\")\n", + "study.optimize(objective, n_trials=200)\n", + "\n", + "best_trial = study.best_trial\n", + "\n", + "print(\"Best trial:\")\n", + "print(f\"F1 Score: {best_trial.value:.6f}\")\n", + "print(\"Parameters:\")\n", + "for k, v in best_trial.params.items():\n", + " print(f\"{k}: {v}\")" + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/dj/6m_rn6_56pvb0zb7k0t6bz4r0000gn/T/ipykernel_1127/3819207535.py:8: DeprecationWarning: Use dataset_load() instead of load_dataset(). load_dataset() will be removed in a future version.\n", - " df = kagglehub.load_dataset(\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**CatBoost results:**" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Downloading from https://www.kaggle.com/api/v1/datasets/download/bhavikjikadara/loan-status-prediction?dataset_version_number=1&file_name=loan_data.csv...\n" - ] + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[I 2025-08-17 17:05:16,870] A new study created in memory with name: no-name-58367467-9a1e-4d65-bfaf-46562a4f4de8\n", + "[I 2025-08-17 17:05:17,646] Trial 0 finished with value: 0.9336826514116986 and parameters: {'iterations': 447, 'depth': 7, 'learning_rate': 0.010022052741993987, 'l2_leaf_reg': 0.00012108855576002585, 'random_strength': 0.0014307171606371407, 'bagging_temperature': 1.2400472888236214, 'border_count': 118, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 67, 'rsm': 0.7492964415768959}. Best is trial 0 with value: 0.9336826514116986.\n", + "[I 2025-08-17 17:05:28,392] Trial 1 finished with value: 0.9357671816047922 and parameters: {'iterations': 320, 'depth': 12, 'learning_rate': 0.005265584834540258, 'l2_leaf_reg': 3.348332251065364e-05, 'random_strength': 0.016130126681163013, 'bagging_temperature': 3.184610728695145, 'border_count': 132, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 16, 'rsm': 0.3661804580910256}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:05:56,176] Trial 2 finished with value: 0.9353286370472839 and parameters: {'iterations': 301, 'depth': 15, 'learning_rate': 0.001229239587857227, 'l2_leaf_reg': 0.24114858700166839, 'random_strength': 3.653421601255403e-08, 'bagging_temperature': 0.268499084758938, 'border_count': 38, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 87, 'rsm': 0.4077894430643999}. Best is trial 1 with value: 0.9357671816047922.\n", + "/Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages/joblib/externals/loky/process_executor.py:782: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n", + " warnings.warn(\n", + "[I 2025-08-17 17:05:59,001] Trial 3 finished with value: 0.9263914470949277 and parameters: {'iterations': 308, 'depth': 8, 'learning_rate': 0.006923745139831324, 'l2_leaf_reg': 2.232447055025466e-05, 'random_strength': 9.589017869992023, 'bagging_temperature': 1.1664981735070379, 'border_count': 244, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 36, 'rsm': 0.2272363033800584}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:05:59,894] Trial 4 finished with value: 0.9307067517478776 and parameters: {'iterations': 384, 'depth': 2, 'learning_rate': 0.006162982787165949, 'l2_leaf_reg': 0.0002455528925686078, 'random_strength': 0.00023861190911366858, 'bagging_temperature': 4.590603297409774, 'border_count': 89, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 43, 'rsm': 0.47744937225955014}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:09:58,626] Trial 5 finished with value: 0.9211242467721258 and parameters: {'iterations': 126, 'depth': 16, 'learning_rate': 0.009746370340105637, 'l2_leaf_reg': 0.00030954644505648175, 'random_strength': 2.429275544391415e-05, 'bagging_temperature': 2.010716645408075, 'border_count': 49, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 13, 'rsm': 0.9165484726032328}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:00,013] Trial 6 finished with value: 0.9279980893054489 and parameters: {'iterations': 304, 'depth': 13, 'learning_rate': 0.002452909941863272, 'l2_leaf_reg': 0.0007960036275127577, 'random_strength': 0.03279083919638105, 'bagging_temperature': 0.11620956490151985, 'border_count': 176, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 90, 'rsm': 0.4918546771049915}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:00,157] Trial 7 finished with value: 0.9033264977789675 and parameters: {'iterations': 118, 'depth': 6, 'learning_rate': 0.0010815676236105107, 'l2_leaf_reg': 2.343577077870732e-06, 'random_strength': 0.19573002126091082, 'bagging_temperature': 9.328816805466154, 'border_count': 92, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 73, 'rsm': 0.7721304474012315}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:01,029] Trial 8 finished with value: 0.9282028882177922 and parameters: {'iterations': 139, 'depth': 13, 'learning_rate': 0.37449386293043335, 'l2_leaf_reg': 1.510385273200855e-07, 'random_strength': 8.805885915613816e-06, 'bagging_temperature': 9.920620684320985, 'border_count': 103, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 82, 'rsm': 0.7133460589949088}. Best is trial 1 with value: 0.9357671816047922.\n", + "[I 2025-08-17 17:10:01,332] Trial 9 finished with value: 0.9478823107512284 and parameters: {'iterations': 442, 'depth': 14, 'learning_rate': 0.017390550482273417, 'l2_leaf_reg': 1.4191517744514907e-08, 'random_strength': 0.08085481833131353, 'bagging_temperature': 0.5861540758081338, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.3057024492058511}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:01,540] Trial 10 finished with value: 0.9387675439474699 and parameters: {'iterations': 483, 'depth': 10, 'learning_rate': 0.06649646241149486, 'l2_leaf_reg': 1.5294498702948475e-08, 'random_strength': 6.457056903771226, 'bagging_temperature': 0.3762360484331467, 'border_count': 185, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 60, 'rsm': 0.1129456685393378}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:01,745] Trial 11 finished with value: 0.9364695961754009 and parameters: {'iterations': 488, 'depth': 10, 'learning_rate': 0.07157332063575793, 'l2_leaf_reg': 1.2340552291844822e-08, 'random_strength': 6.8475165988578945, 'bagging_temperature': 0.41833481531429084, 'border_count': 183, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 57, 'rsm': 0.12225677733328608}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:01,879] Trial 12 finished with value: 0.9420281633568404 and parameters: {'iterations': 401, 'depth': 10, 'learning_rate': 0.04705474327284803, 'l2_leaf_reg': 4.619135274034043e-08, 'random_strength': 0.2877962903926624, 'bagging_temperature': 0.4410061869425525, 'border_count': 183, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.10497821047560195}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,057] Trial 13 finished with value: 0.9392165631469979 and parameters: {'iterations': 401, 'depth': 4, 'learning_rate': 0.035092587572258575, 'l2_leaf_reg': 7.418402902502616e-07, 'random_strength': 0.24279060329838162, 'bagging_temperature': 0.550265277142082, 'border_count': 223, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.2912361775318139}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,163] Trial 14 finished with value: 0.9332145859168754 and parameters: {'iterations': 196, 'depth': 11, 'learning_rate': 0.20424392007978667, 'l2_leaf_reg': 0.07259273690884574, 'random_strength': 0.445044262919236, 'bagging_temperature': 0.16497562046877015, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.2189011845729476}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,465] Trial 15 finished with value: 0.942245284348707 and parameters: {'iterations': 396, 'depth': 14, 'learning_rate': 0.023781291427423204, 'l2_leaf_reg': 9.270565187606277, 'random_strength': 0.0038796338897692183, 'bagging_temperature': 0.6361579144475542, 'border_count': 205, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 77, 'rsm': 0.29776900392803746}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:02,727] Trial 16 finished with value: 0.9394832914849566 and parameters: {'iterations': 234, 'depth': 14, 'learning_rate': 0.025406716067111187, 'l2_leaf_reg': 0.00940902288686199, 'random_strength': 0.0011467692702004809, 'bagging_temperature': 0.9288491682156569, 'border_count': 217, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 79, 'rsm': 0.3312745395954699}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:03,328] Trial 17 finished with value: 0.9364990440949738 and parameters: {'iterations': 364, 'depth': 16, 'learning_rate': 0.01459315336705923, 'l2_leaf_reg': 1.5017720263656562, 'random_strength': 2.168129156965766e-07, 'bagging_temperature': 0.7031608622072022, 'border_count': 161, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 68, 'rsm': 0.579429591294561}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:04,579] Trial 18 finished with value: 0.9336769052166423 and parameters: {'iterations': 437, 'depth': 14, 'learning_rate': 0.09335993870933126, 'l2_leaf_reg': 0.009070739751415742, 'random_strength': 0.011596516896850755, 'bagging_temperature': 0.21831142466765102, 'border_count': 217, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 31, 'rsm': 0.6254526681385288}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:04,966] Trial 19 finished with value: 0.9452204073242001 and parameters: {'iterations': 345, 'depth': 12, 'learning_rate': 0.018942551364461224, 'l2_leaf_reg': 7.3406357956098915, 'random_strength': 7.810547328849867e-05, 'bagging_temperature': 2.592739930745042, 'border_count': 254, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 51, 'rsm': 0.2411083987489646}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:05,836] Trial 20 finished with value: 0.9416257250171322 and parameters: {'iterations': 238, 'depth': 12, 'learning_rate': 0.16297331414932478, 'l2_leaf_reg': 3.20532030293621e-06, 'random_strength': 2.667508753112458e-05, 'bagging_temperature': 1.9944880335976674, 'border_count': 248, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 1, 'rsm': 0.19965980630801725}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:06,233] Trial 21 finished with value: 0.9394580121286875 and parameters: {'iterations': 354, 'depth': 14, 'learning_rate': 0.021032869203904486, 'l2_leaf_reg': 8.092710664822752, 'random_strength': 0.0001705884950621921, 'bagging_temperature': 2.0769627719799915, 'border_count': 204, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 50, 'rsm': 0.2886138656825273}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:06,725] Trial 22 finished with value: 0.9422897581604335 and parameters: {'iterations': 427, 'depth': 12, 'learning_rate': 0.01728066242461722, 'l2_leaf_reg': 8.28487233199894, 'random_strength': 2.149716909747561e-06, 'bagging_temperature': 0.8352506132748097, 'border_count': 251, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 75, 'rsm': 0.42775896559818366}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:06,823] Trial 23 finished with value: 0.9278465391707099 and parameters: {'iterations': 54, 'depth': 9, 'learning_rate': 0.0034815878598868596, 'l2_leaf_reg': 0.5205208963206108, 'random_strength': 1.4520874032939126e-06, 'bagging_temperature': 4.7210870436758015, 'border_count': 255, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 56, 'rsm': 0.4280559895016039}. Best is trial 9 with value: 0.9478823107512284.\n", + "[I 2025-08-17 17:10:07,101] Trial 24 finished with value: 0.9479595700629927 and parameters: {'iterations': 439, 'depth': 11, 'learning_rate': 0.014527673079264242, 'l2_leaf_reg': 0.04052582749131081, 'random_strength': 7.707152529842055e-07, 'bagging_temperature': 1.0117939040088955, 'border_count': 66, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 66, 'rsm': 0.5153902213295005}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:07,491] Trial 25 finished with value: 0.9363015933085312 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.011466713691318525, 'l2_leaf_reg': 0.07842092575522967, 'random_strength': 1.622972705803686e-08, 'bagging_temperature': 1.328255947976371, 'border_count': 67, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 48, 'rsm': 0.536170510768572}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:07,817] Trial 26 finished with value: 0.9335191724299957 and parameters: {'iterations': 461, 'depth': 9, 'learning_rate': 0.0429759330516577, 'l2_leaf_reg': 0.004048148753961586, 'random_strength': 3.7632379882557923e-07, 'bagging_temperature': 3.403927830806352, 'border_count': 69, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 64, 'rsm': 0.6525305409485735}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:08,358] Trial 27 finished with value: 0.9282013843144794 and parameters: {'iterations': 350, 'depth': 6, 'learning_rate': 0.003882869945542356, 'l2_leaf_reg': 0.05588647211639355, 'random_strength': 6.359930947232507e-05, 'bagging_temperature': 1.4592262498420976, 'border_count': 131, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 34, 'rsm': 0.9793885580992495}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:08,548] Trial 28 finished with value: 0.9420309049149707 and parameters: {'iterations': 425, 'depth': 11, 'learning_rate': 0.029726236281782142, 'l2_leaf_reg': 1.5338456392901354, 'random_strength': 3.743821948231872e-06, 'bagging_temperature': 2.9080001491398706, 'border_count': 62, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 44, 'rsm': 0.17938436731862395}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:08,873] Trial 29 finished with value: 0.9422389645096398 and parameters: {'iterations': 464, 'depth': 13, 'learning_rate': 0.009239537495248366, 'l2_leaf_reg': 0.0016581052501387665, 'random_strength': 0.0010903132600641387, 'bagging_temperature': 5.8823898983566085, 'border_count': 117, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 68, 'rsm': 0.369621859571436}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:09,187] Trial 30 finished with value: 0.9396483121154722 and parameters: {'iterations': 330, 'depth': 8, 'learning_rate': 0.014443547745130356, 'l2_leaf_reg': 1.439392094711217, 'random_strength': 3.739301341196257e-07, 'bagging_temperature': 0.308963668790458, 'border_count': 111, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 85, 'rsm': 0.8015034073072183}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:09,647] Trial 31 finished with value: 0.9364292909269782 and parameters: {'iterations': 431, 'depth': 12, 'learning_rate': 0.016172687028915955, 'l2_leaf_reg': 9.851796326883738, 'random_strength': 1.5263901772318894e-06, 'bagging_temperature': 0.8713768131029922, 'border_count': 236, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 71, 'rsm': 0.46762344504636993}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 17:10:10,098] Trial 32 finished with value: 0.9420281633568404 and parameters: {'iterations': 422, 'depth': 12, 'learning_rate': 0.019237803571276867, 'l2_leaf_reg': 5.64247056264795e-05, 'random_strength': 1.110832663151052e-07, 'bagging_temperature': 0.769726648591094, 'border_count': 234, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 62, 'rsm': 0.3888529760016267}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:45,302] Trial 33 finished with value: 0.938692385540542 and parameters: {'iterations': 463, 'depth': 15, 'learning_rate': 0.009645280889137171, 'l2_leaf_reg': 0.35813648095480866, 'random_strength': 2.6469075432648367e-06, 'bagging_temperature': 0.5215296142925352, 'border_count': 130, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 76, 'rsm': 0.5297182093386201}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:46,696] Trial 34 finished with value: 0.941986075759133 and parameters: {'iterations': 382, 'depth': 15, 'learning_rate': 0.007461286652302521, 'l2_leaf_reg': 0.045944207061274785, 'random_strength': 1.1780126052966517e-05, 'bagging_temperature': 1.1591340186781007, 'border_count': 35, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 54, 'rsm': 0.4292186056059847}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:54,557] Trial 35 finished with value: 0.938692385540542 and parameters: {'iterations': 323, 'depth': 12, 'learning_rate': 0.005100615830139832, 'l2_leaf_reg': 2.76900031010676, 'random_strength': 4.188228359346592e-08, 'bagging_temperature': 1.747951669619372, 'border_count': 146, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 91, 'rsm': 0.26684788997918296}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:57:55,361] Trial 36 finished with value: 0.9302795905288737 and parameters: {'iterations': 253, 'depth': 1, 'learning_rate': 0.039079338269258676, 'l2_leaf_reg': 0.3264818328644774, 'random_strength': 0.0001884997641458613, 'bagging_temperature': 2.7785286733195584, 'border_count': 201, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 65, 'rsm': 0.583038894597953}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:58:22,055] Trial 37 finished with value: 0.9388894809828734 and parameters: {'iterations': 280, 'depth': 13, 'learning_rate': 0.014094418061125095, 'l2_leaf_reg': 3.908286333679212, 'random_strength': 8.958686737872702e-05, 'bagging_temperature': 1.032578356936754, 'border_count': 237, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 42, 'rsm': 0.3272909714423266}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:58:23,234] Trial 38 finished with value: 0.9364990440949738 and parameters: {'iterations': 365, 'depth': 11, 'learning_rate': 0.060059916793946344, 'l2_leaf_reg': 7.868576296018248e-06, 'random_strength': 6.792612118084799e-07, 'bagging_temperature': 1.5912784757409366, 'border_count': 166, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.4652304438594406}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 18:58:24,209] Trial 39 finished with value: 0.9366516728480241 and parameters: {'iterations': 446, 'depth': 7, 'learning_rate': 0.002658865746535032, 'l2_leaf_reg': 0.00011552756384141058, 'random_strength': 0.0005168873823892629, 'bagging_temperature': 0.2564675614174855, 'border_count': 79, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 83, 'rsm': 0.16741994023948076}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:40,334] Trial 40 finished with value: 0.9145144021182363 and parameters: {'iterations': 416, 'depth': 16, 'learning_rate': 0.001625377939477702, 'l2_leaf_reg': 0.01695192283696182, 'random_strength': 1.2800588262812822, 'bagging_temperature': 2.460206131631878, 'border_count': 44, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 28, 'rsm': 0.35901664766904245}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:42,002] Trial 41 finished with value: 0.9392165631469979 and parameters: {'iterations': 389, 'depth': 15, 'learning_rate': 0.025079439069078373, 'l2_leaf_reg': 0.6243249540865272, 'random_strength': 0.006997599154730658, 'bagging_temperature': 0.5911520319919781, 'border_count': 198, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.25415982233413037}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:42,934] Trial 42 finished with value: 0.9392165631469979 and parameters: {'iterations': 406, 'depth': 13, 'learning_rate': 0.02054123087754466, 'l2_leaf_reg': 3.919564761634939, 'random_strength': 0.055677410426894, 'bagging_temperature': 0.6517074553530903, 'border_count': 225, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 77, 'rsm': 0.3298616390415405}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:43,845] Trial 43 finished with value: 0.942125092874029 and parameters: {'iterations': 378, 'depth': 14, 'learning_rate': 0.007026342264096326, 'l2_leaf_reg': 8.711730483641022, 'random_strength': 0.00472664123555551, 'bagging_temperature': 0.3446434221110068, 'border_count': 255, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.4312689437069658}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:44,922] Trial 44 finished with value: 0.9450707105413858 and parameters: {'iterations': 473, 'depth': 10, 'learning_rate': 0.027681440661557893, 'l2_leaf_reg': 0.18291973999173342, 'random_strength': 0.00325240166416229, 'bagging_temperature': 0.4897789674798157, 'border_count': 210, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.4990356400478725}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:45,274] Trial 45 finished with value: 0.9448535895495193 and parameters: {'iterations': 479, 'depth': 10, 'learning_rate': 0.029930321385175925, 'l2_leaf_reg': 0.18263997781920413, 'random_strength': 7.949010143906268e-06, 'bagging_temperature': 0.4895403089803191, 'border_count': 96, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.5238484162127857}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:45,768] Trial 46 finished with value: 0.9364356107660455 and parameters: {'iterations': 482, 'depth': 10, 'learning_rate': 0.10487991736828609, 'l2_leaf_reg': 0.14015721097061587, 'random_strength': 0.06871745384141728, 'bagging_temperature': 0.498601333720442, 'border_count': 92, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 59, 'rsm': 0.718638239457858}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:46,074] Trial 47 finished with value: 0.9363079131475986 and parameters: {'iterations': 474, 'depth': 9, 'learning_rate': 0.05448482436597816, 'l2_leaf_reg': 0.0007508312150194058, 'random_strength': 1.979400992759582e-05, 'bagging_temperature': 0.21002891587474082, 'border_count': 53, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 70, 'rsm': 0.6263174952857236}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:46,353] Trial 48 finished with value: 0.936230298491723 and parameters: {'iterations': 449, 'depth': 7, 'learning_rate': 0.03372017360451665, 'l2_leaf_reg': 0.02508232620466937, 'random_strength': 0.02516944698482475, 'bagging_temperature': 0.40295412254807156, 'border_count': 78, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 53, 'rsm': 0.5170308825970374}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:46,687] Trial 49 finished with value: 0.9448535895495193 and parameters: {'iterations': 491, 'depth': 10, 'learning_rate': 0.029047803839886373, 'l2_leaf_reg': 0.12411530275943795, 'random_strength': 8.287968664356238e-06, 'bagging_temperature': 0.46420002877368444, 'border_count': 99, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.576394702785206}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:47,079] Trial 50 finished with value: 0.9335149171108468 and parameters: {'iterations': 449, 'depth': 8, 'learning_rate': 0.012384714014048469, 'l2_leaf_reg': 4.3977186402650976e-07, 'random_strength': 0.002271373832260034, 'bagging_temperature': 0.1043542172721108, 'border_count': 82, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 61, 'rsm': 0.8253111118684651}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:47,501] Trial 51 finished with value: 0.9452420510109686 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.03232589786063133, 'l2_leaf_reg': 0.19703798265346817, 'random_strength': 5.682342586106171e-06, 'bagging_temperature': 0.4457314732827191, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.5727499927098123}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:48,019] Trial 52 finished with value: 0.9448457718455867 and parameters: {'iterations': 499, 'depth': 11, 'learning_rate': 0.08201361984215827, 'l2_leaf_reg': 0.002668078344401463, 'random_strength': 7.629588890045705e-06, 'bagging_temperature': 0.37097420807829845, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 86, 'rsm': 0.6786931996465365}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:48,422] Trial 53 finished with value: 0.9451013583702761 and parameters: {'iterations': 476, 'depth': 11, 'learning_rate': 0.04256451322092073, 'l2_leaf_reg': 0.18609798645826242, 'random_strength': 4.354965293869604e-05, 'bagging_temperature': 0.2870688189555022, 'border_count': 118, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.4929604048578121}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:48,908] Trial 54 finished with value: 0.9422897581604335 and parameters: {'iterations': 464, 'depth': 13, 'learning_rate': 0.04639776081891739, 'l2_leaf_reg': 0.7666153446391908, 'random_strength': 7.476609311900428e-05, 'bagging_temperature': 0.18093394455307654, 'border_count': 122, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.4812218350798194}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:49,360] Trial 55 finished with value: 0.9420419893396765 and parameters: {'iterations': 444, 'depth': 11, 'learning_rate': 0.12177647073574174, 'l2_leaf_reg': 0.025253511131175507, 'random_strength': 0.0004968302143202226, 'bagging_temperature': 0.29574922923916513, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.5800214751972506}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:49,481] Trial 56 finished with value: 0.9303835174168823 and parameters: {'iterations': 179, 'depth': 9, 'learning_rate': 0.4804592339834937, 'l2_leaf_reg': 4.29374260688016e-08, 'random_strength': 2.1023104425356554e-05, 'bagging_temperature': 0.15252719973624834, 'border_count': 189, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.23538528068494383}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:49,935] Trial 57 finished with value: 0.9391606495664544 and parameters: {'iterations': 409, 'depth': 12, 'learning_rate': 0.03858242532556046, 'l2_leaf_reg': 0.0005243163656055302, 'random_strength': 0.90882557493314, 'bagging_temperature': 0.2467396953084091, 'border_count': 172, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.6205511157155944}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,111] Trial 58 finished with value: 0.9450568845585497 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.022903344954733652, 'l2_leaf_reg': 0.0050895313793075285, 'random_strength': 3.959400177014319e-05, 'bagging_temperature': 7.691139508185991, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.14328631200347425}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,358] Trial 59 finished with value: 0.9449614966901738 and parameters: {'iterations': 288, 'depth': 10, 'learning_rate': 0.052270626553195046, 'l2_leaf_reg': 0.015183999507432818, 'random_strength': 0.0003193911671015348, 'bagging_temperature': 0.7215808592563201, 'border_count': 158, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.5051907715975001}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,626] Trial 60 finished with value: 0.9392610369587242 and parameters: {'iterations': 337, 'depth': 12, 'learning_rate': 0.07355185141560906, 'l2_leaf_reg': 0.20196677808219077, 'random_strength': 9.173337953915923e-07, 'bagging_temperature': 1.076397502882221, 'border_count': 139, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.5483613280711558}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:50,786] Trial 61 finished with value: 0.9450568845585497 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.022503958124257865, 'l2_leaf_reg': 0.0053822010708529785, 'random_strength': 3.6788525900741224e-06, 'bagging_temperature': 8.340087130052538, 'border_count': 110, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.14046713436027425}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,001] Trial 62 finished with value: 0.9450568845585497 and parameters: {'iterations': 458, 'depth': 11, 'learning_rate': 0.01689186112137248, 'l2_leaf_reg': 0.05213905679989868, 'random_strength': 5.761360055878985e-05, 'bagging_temperature': 3.8785298751967336, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 84, 'rsm': 0.21604658939588595}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,151] Trial 63 finished with value: 0.9451013583702761 and parameters: {'iterations': 489, 'depth': 4, 'learning_rate': 0.0109998556655596, 'l2_leaf_reg': 0.0015933889574844828, 'random_strength': 3.7107547701043355e-05, 'bagging_temperature': 0.5750351844280351, 'border_count': 112, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.17440247613480278}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,325] Trial 64 finished with value: 0.9394580121286875 and parameters: {'iterations': 497, 'depth': 4, 'learning_rate': 0.008862185692537406, 'l2_leaf_reg': 0.0001616306852051432, 'random_strength': 0.0001253545848135207, 'bagging_temperature': 0.5809952238061248, 'border_count': 87, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.39211824641718424}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:51,557] Trial 65 finished with value: 0.9450568845585497 and parameters: {'iterations': 441, 'depth': 4, 'learning_rate': 0.01927073249172679, 'l2_leaf_reg': 0.8886683537672693, 'random_strength': 0.0009200433649419209, 'bagging_temperature': 0.3258586539625712, 'border_count': 147, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 22, 'rsm': 0.25435277879936763}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:53,561] Trial 66 finished with value: 0.9330174904745441 and parameters: {'iterations': 431, 'depth': 8, 'learning_rate': 0.01121881943404954, 'l2_leaf_reg': 0.001891135856776816, 'random_strength': 0.10334570071942178, 'bagging_temperature': 0.3935708768450864, 'border_count': 215, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 90, 'rsm': 0.19210065058904802}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:54,625] Trial 67 finished with value: 0.9450147969608423 and parameters: {'iterations': 484, 'depth': 3, 'learning_rate': 0.00579402157241798, 'l2_leaf_reg': 0.35127082993071396, 'random_strength': 0.010864405142117882, 'bagging_temperature': 0.7519525888035951, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 67, 'rsm': 0.45408506228049234}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:55,591] Trial 68 finished with value: 0.9391606495664544 and parameters: {'iterations': 459, 'depth': 9, 'learning_rate': 0.012411149890886005, 'l2_leaf_reg': 1.6764351896435874e-05, 'random_strength': 1.310790266546465e-07, 'bagging_temperature': 0.45145858949881645, 'border_count': 55, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 46, 'rsm': 0.3014763801342136}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,469] Trial 69 finished with value: 0.9369181533853135 and parameters: {'iterations': 418, 'depth': 6, 'learning_rate': 0.008387464067222912, 'l2_leaf_reg': 0.08155285274527148, 'random_strength': 0.002509110127115399, 'bagging_temperature': 0.9268562138535151, 'border_count': 71, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.6003005382283918}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,572] Trial 70 finished with value: 0.9390625201399484 and parameters: {'iterations': 309, 'depth': 1, 'learning_rate': 0.03329871150014482, 'l2_leaf_reg': 2.2276605358743353, 'random_strength': 4.9898598389615e-06, 'bagging_temperature': 0.6419929476777696, 'border_count': 106, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 100, 'rsm': 0.49360370831141787}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,743] Trial 71 finished with value: 0.9392165631469979 and parameters: {'iterations': 471, 'depth': 10, 'learning_rate': 0.0252888738684369, 'l2_leaf_reg': 0.005017507709629204, 'random_strength': 2.440068851809699e-05, 'bagging_temperature': 6.3294777334946986, 'border_count': 114, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.14864350704014634}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:56,916] Trial 72 finished with value: 0.9420281633568404 and parameters: {'iterations': 488, 'depth': 12, 'learning_rate': 0.01827112156919407, 'l2_leaf_reg': 0.0014745826355574527, 'random_strength': 3.275792525199124e-05, 'bagging_temperature': 1.276778289508142, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.15087933871697753}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:57,089] Trial 73 finished with value: 0.9420281633568404 and parameters: {'iterations': 475, 'depth': 11, 'learning_rate': 0.042064077989929866, 'l2_leaf_reg': 0.0074787463668816384, 'random_strength': 1.2921631502648065e-05, 'bagging_temperature': 6.807420909116351, 'border_count': 135, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 90, 'rsm': 0.11210268157392836}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:57,572] Trial 74 finished with value: 0.9392165631469979 and parameters: {'iterations': 453, 'depth': 13, 'learning_rate': 0.014324211383182505, 'l2_leaf_reg': 0.01112135218539427, 'random_strength': 4.1357270748163564e-05, 'bagging_temperature': 4.490330592421232, 'border_count': 242, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 39, 'rsm': 0.20919152340585995}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:57,991] Trial 75 finished with value: 0.9422897581604335 and parameters: {'iterations': 436, 'depth': 14, 'learning_rate': 0.02827315737020178, 'l2_leaf_reg': 0.03221556524852036, 'random_strength': 0.00011592539358124591, 'bagging_temperature': 0.2803768481383997, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.663939368673399}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:15:58,177] Trial 76 finished with value: 0.9450568845585497 and parameters: {'iterations': 498, 'depth': 5, 'learning_rate': 0.021987917437276475, 'l2_leaf_reg': 0.00028929465695989555, 'random_strength': 0.0004455219763426272, 'bagging_temperature': 0.5433075891499852, 'border_count': 100, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 86, 'rsm': 0.1814060619681274}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:00,880] Trial 77 finished with value: 0.9330813491825122 and parameters: {'iterations': 396, 'depth': 10, 'learning_rate': 0.01589601631670435, 'l2_leaf_reg': 0.0340153617396941, 'random_strength': 0.00022120378185857412, 'bagging_temperature': 0.8333005477979103, 'border_count': 108, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 79, 'rsm': 0.2740591686694898}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,054] Trial 78 finished with value: 0.9362630839917611 and parameters: {'iterations': 486, 'depth': 12, 'learning_rate': 0.01250814432155388, 'l2_leaf_reg': 0.08597019771125995, 'random_strength': 3.875658497816237, 'bagging_temperature': 2.027781613667445, 'border_count': 228, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.554428285548262}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,477] Trial 79 finished with value: 0.9332999610216076 and parameters: {'iterations': 470, 'depth': 13, 'learning_rate': 0.03479471943998336, 'l2_leaf_reg': 0.0011038001978353085, 'random_strength': 1.4623871246898063e-06, 'bagging_temperature': 8.298637491032066, 'border_count': 86, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 1, 'rsm': 0.10575314391531795}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,578] Trial 80 finished with value: 0.930715608357473 and parameters: {'iterations': 64, 'depth': 11, 'learning_rate': 0.009970381997329417, 'l2_leaf_reg': 0.002457657979958449, 'random_strength': 5.006664611985971e-07, 'bagging_temperature': 0.3480378302514736, 'border_count': 195, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 83, 'rsm': 0.35085888320037617}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,759] Trial 81 finished with value: 0.939247210975888 and parameters: {'iterations': 474, 'depth': 11, 'learning_rate': 0.023021073395322878, 'l2_leaf_reg': 0.00501303583428343, 'random_strength': 3.297609176261554e-06, 'bagging_temperature': 9.116387247059526, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.1602471439901559}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:02,945] Trial 82 finished with value: 0.9422759321775974 and parameters: {'iterations': 455, 'depth': 11, 'learning_rate': 0.021341812343129634, 'l2_leaf_reg': 0.0032786030922662217, 'random_strength': 5.6167075068437285e-06, 'bagging_temperature': 7.001846826723126, 'border_count': 93, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.23565806187990584}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,131] Trial 83 finished with value: 0.9450568845585497 and parameters: {'iterations': 486, 'depth': 9, 'learning_rate': 0.025481031559351847, 'l2_leaf_reg': 0.00044861252069219073, 'random_strength': 1.3602639637159673e-05, 'bagging_temperature': 5.269525570746078, 'border_count': 210, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.12292909475376332}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,339] Trial 84 finished with value: 0.9421893707681634 and parameters: {'iterations': 467, 'depth': 10, 'learning_rate': 0.017194280312834556, 'l2_leaf_reg': 0.007334290737691393, 'random_strength': 2.3345258144382588e-06, 'bagging_temperature': 7.5185445722122735, 'border_count': 128, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 57, 'rsm': 0.14168837872160733}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,649] Trial 85 finished with value: 0.9391606495664544 and parameters: {'iterations': 436, 'depth': 10, 'learning_rate': 0.06135057142926861, 'l2_leaf_reg': 0.015040042311610397, 'random_strength': 3.579764468234165e-05, 'bagging_temperature': 9.828877956015381, 'border_count': 121, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 51, 'rsm': 0.3120321567349598}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,749] Trial 86 finished with value: 0.9334278799514462 and parameters: {'iterations': 255, 'depth': 2, 'learning_rate': 0.010786695590314385, 'l2_leaf_reg': 0.24367622394113866, 'random_strength': 8.993969123072843e-07, 'bagging_temperature': 5.586430695006047, 'border_count': 134, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 93, 'rsm': 0.44661208004691777}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:03,883] Trial 87 finished with value: 0.9420281633568404 and parameters: {'iterations': 422, 'depth': 12, 'learning_rate': 0.029876299308035606, 'l2_leaf_reg': 0.5101805055124192, 'random_strength': 1.6028254589219494e-05, 'bagging_temperature': 2.347165672173358, 'border_count': 74, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 95, 'rsm': 0.13709507722446973}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:04,057] Trial 88 finished with value: 0.9420281633568404 and parameters: {'iterations': 500, 'depth': 12, 'learning_rate': 0.04807108394354161, 'l2_leaf_reg': 0.13790292373355792, 'random_strength': 2.632778506093437e-07, 'bagging_temperature': 3.569452748252071, 'border_count': 65, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.17151325317899663}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:04,169] Trial 89 finished with value: 0.9392610369587242 and parameters: {'iterations': 209, 'depth': 11, 'learning_rate': 0.013899379180866756, 'l2_leaf_reg': 1.1783486548788338, 'random_strength': 5.439814781017007e-05, 'bagging_temperature': 0.42528108214495586, 'border_count': 113, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 90, 'rsm': 0.20735459506567905}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:09,781] Trial 90 finished with value: 0.9270999046522576 and parameters: {'iterations': 478, 'depth': 9, 'learning_rate': 0.037845787355695625, 'l2_leaf_reg': 2.6515688541607453e-06, 'random_strength': 0.00010733387818114766, 'bagging_temperature': 0.22473932776660133, 'border_count': 174, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 78, 'rsm': 0.5545889385122719}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:10,910] Trial 91 finished with value: 0.9420281633568404 and parameters: {'iterations': 457, 'depth': 11, 'learning_rate': 0.01687742839839296, 'l2_leaf_reg': 0.058337034137483715, 'random_strength': 6.0975438635664064e-05, 'bagging_temperature': 3.8481206713620297, 'border_count': 121, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 85, 'rsm': 0.23247169942382973}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:11,158] Trial 92 finished with value: 0.942245284348707 and parameters: {'iterations': 445, 'depth': 11, 'learning_rate': 0.020355212143055232, 'l2_leaf_reg': 0.051207521743224876, 'random_strength': 4.4117960211688904e-06, 'bagging_temperature': 4.116640848888592, 'border_count': 126, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 84, 'rsm': 0.21191224274175083}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:12,071] Trial 93 finished with value: 0.9392165631469979 and parameters: {'iterations': 464, 'depth': 10, 'learning_rate': 0.026718910027624717, 'l2_leaf_reg': 0.021701446878278626, 'random_strength': 0.0003112530044111786, 'bagging_temperature': 8.294352455693376, 'border_count': 100, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 64, 'rsm': 0.19123093114228457}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:12,954] Trial 94 finished with value: 0.9420281633568404 and parameters: {'iterations': 489, 'depth': 11, 'learning_rate': 0.014921326317568194, 'l2_leaf_reg': 0.10684023710190069, 'random_strength': 0.00015629124932698926, 'bagging_temperature': 1.5913711380912872, 'border_count': 108, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.12680316028591293}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,154] Trial 95 finished with value: 0.9422897581604335 and parameters: {'iterations': 366, 'depth': 15, 'learning_rate': 0.007724090791156113, 'l2_leaf_reg': 4.970487705297225, 'random_strength': 4.832812376313844e-05, 'bagging_temperature': 2.996806980720935, 'border_count': 118, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 91, 'rsm': 0.25001746171887856}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,408] Trial 96 finished with value: 0.9478629958899154 and parameters: {'iterations': 454, 'depth': 13, 'learning_rate': 0.03206259992239698, 'l2_leaf_reg': 9.747885664977631e-07, 'random_strength': 0.0007036688892877016, 'bagging_temperature': 0.676762062406568, 'border_count': 141, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.2828976991951257}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,567] Trial 97 finished with value: 0.944516944120737 and parameters: {'iterations': 431, 'depth': 14, 'learning_rate': 0.03596250183653654, 'l2_leaf_reg': 2.6049742839678903e-08, 'random_strength': 0.0008507615097739611, 'bagging_temperature': 0.6858858531994815, 'border_count': 43, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 81, 'rsm': 0.2866478375723365}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:13,860] Trial 98 finished with value: 0.9420281633568404 and parameters: {'iterations': 407, 'depth': 13, 'learning_rate': 0.032590080256233785, 'l2_leaf_reg': 5.3306992270388546e-06, 'random_strength': 0.022674287404467704, 'bagging_temperature': 0.6170819475854629, 'border_count': 166, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.5047854521017533}. Best is trial 24 with value: 0.9479595700629927.\n", + "[I 2025-08-17 19:16:15,792] Trial 99 finished with value: 0.948099087498995 and parameters: {'iterations': 478, 'depth': 12, 'learning_rate': 0.04254101358886379, 'l2_leaf_reg': 1.7277473564532868e-07, 'random_strength': 0.0019440779833289569, 'bagging_temperature': 0.5084286556246295, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 7, 'rsm': 0.37971137763889}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:17,725] Trial 100 finished with value: 0.9421995038264234 and parameters: {'iterations': 447, 'depth': 13, 'learning_rate': 0.054553627666991615, 'l2_leaf_reg': 1.9031563366687202e-07, 'random_strength': 0.001478569010347561, 'bagging_temperature': 0.5020127547283775, 'border_count': 180, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 8, 'rsm': 0.3985919741588475}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:18,099] Trial 101 finished with value: 0.938893699917104 and parameters: {'iterations': 473, 'depth': 12, 'learning_rate': 0.04289147265365806, 'l2_leaf_reg': 7.177530776956312e-08, 'random_strength': 0.005112570354371122, 'bagging_temperature': 0.8041822809136442, 'border_count': 153, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 67, 'rsm': 0.3425524641203796}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:18,829] Trial 102 finished with value: 0.933263873412859 and parameters: {'iterations': 491, 'depth': 12, 'learning_rate': 0.02226381223292443, 'l2_leaf_reg': 9.120516127702251e-07, 'random_strength': 0.0025444221342604914, 'bagging_temperature': 0.564255198899972, 'border_count': 142, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 19, 'rsm': 0.31732954534178587}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:19,365] Trial 103 finished with value: 0.9363490493566118 and parameters: {'iterations': 481, 'depth': 13, 'learning_rate': 0.02483206298542291, 'l2_leaf_reg': 1.5137385022985336e-08, 'random_strength': 0.0007757331181904254, 'bagging_temperature': 0.45248966491294457, 'border_count': 134, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 34, 'rsm': 0.38005525681900953}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:19,840] Trial 104 finished with value: 0.9449682921457203 and parameters: {'iterations': 460, 'depth': 12, 'learning_rate': 0.018505965152376395, 'l2_leaf_reg': 1.5186867963902818e-06, 'random_strength': 0.0015299099277733435, 'bagging_temperature': 0.9604435343858411, 'border_count': 151, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 59, 'rsm': 0.48182633166282013}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:20,085] Trial 105 finished with value: 0.9420419893396765 and parameters: {'iterations': 467, 'depth': 14, 'learning_rate': 0.02999292909768791, 'l2_leaf_reg': 1.0164054698257947e-07, 'random_strength': 0.009267200470185082, 'bagging_temperature': 0.3598497578581198, 'border_count': 104, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.41010965813067535}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:20,351] Trial 106 finished with value: 0.9478823107512284 and parameters: {'iterations': 414, 'depth': 13, 'learning_rate': 0.07309614882931127, 'l2_leaf_reg': 0.0008543057718065979, 'random_strength': 0.0002524560160550367, 'bagging_temperature': 0.4071297784570186, 'border_count': 162, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.266369881554506}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:20,608] Trial 107 finished with value: 0.936463886811552 and parameters: {'iterations': 440, 'depth': 13, 'learning_rate': 0.08190444773381277, 'l2_leaf_reg': 3.214319388206344e-07, 'random_strength': 0.0002612129001674984, 'bagging_temperature': 0.3890984495007036, 'border_count': 147, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 75, 'rsm': 0.270903538495802}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:21,136] Trial 108 finished with value: 0.9308553916078927 and parameters: {'iterations': 416, 'depth': 15, 'learning_rate': 0.10695383481205312, 'l2_leaf_reg': 0.0008919146734425161, 'random_strength': 0.0006207710545904959, 'bagging_temperature': 0.317566864479746, 'border_count': 160, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 70, 'rsm': 0.538778533244966}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:21,430] Trial 109 finished with value: 0.9420281633568404 and parameters: {'iterations': 427, 'depth': 14, 'learning_rate': 0.1469107367152301, 'l2_leaf_reg': 4.444931506830675e-05, 'random_strength': 0.4306633649575429, 'bagging_temperature': 0.535895207806519, 'border_count': 139, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.28942940342239365}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:47,562] Trial 110 finished with value: 0.9141406149187812 and parameters: {'iterations': 393, 'depth': 12, 'learning_rate': 0.0701156386030421, 'l2_leaf_reg': 1.0446575978813497e-08, 'random_strength': 0.003101478071164495, 'bagging_temperature': 0.4225179746298636, 'border_count': 191, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 77, 'rsm': 0.5676355322007246}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:49,102] Trial 111 finished with value: 0.9392980046266818 and parameters: {'iterations': 452, 'depth': 11, 'learning_rate': 0.04157548503684166, 'l2_leaf_reg': 9.034305302437844e-05, 'random_strength': 0.0004057322184259633, 'bagging_temperature': 0.6827176480053725, 'border_count': 167, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 63, 'rsm': 0.3691644950908456}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:50,073] Trial 112 finished with value: 0.9333191418502012 and parameters: {'iterations': 494, 'depth': 12, 'learning_rate': 0.05012391268407289, 'l2_leaf_reg': 2.2291361780007068e-08, 'random_strength': 8.462194507039125e-05, 'bagging_temperature': 0.4730541412136414, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 66, 'rsm': 0.24758489842870557}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:51,388] Trial 113 finished with value: 0.9365108528125179 and parameters: {'iterations': 479, 'depth': 10, 'learning_rate': 0.012897399835445968, 'l2_leaf_reg': 0.0004444637160149302, 'random_strength': 2.21707333469302e-05, 'bagging_temperature': 0.5854775168313623, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 29, 'rsm': 0.6010628227303336}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:52,318] Trial 114 finished with value: 0.9423468716502944 and parameters: {'iterations': 470, 'depth': 13, 'learning_rate': 0.061018518512915516, 'l2_leaf_reg': 0.0015083083238610587, 'random_strength': 0.00015939256236599907, 'bagging_temperature': 0.497044168127894, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 88, 'rsm': 0.5157982122697622}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:52,675] Trial 115 finished with value: 0.9449308488612835 and parameters: {'iterations': 453, 'depth': 14, 'learning_rate': 0.019576894417447522, 'l2_leaf_reg': 0.00017465568855511566, 'random_strength': 1.0722231591328903e-05, 'bagging_temperature': 0.7402991352316811, 'border_count': 156, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 82, 'rsm': 0.4158043971131127}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:52,876] Trial 116 finished with value: 0.9420281633568404 and parameters: {'iterations': 482, 'depth': 11, 'learning_rate': 0.023401534386045135, 'l2_leaf_reg': 0.0041277449321686505, 'random_strength': 0.16395534032321624, 'bagging_temperature': 0.39074084924312, 'border_count': 229, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 99, 'rsm': 0.16361722425973954}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,110] Trial 117 finished with value: 0.9450568845585497 and parameters: {'iterations': 439, 'depth': 12, 'learning_rate': 0.03149277628843053, 'l2_leaf_reg': 0.01123676927285539, 'random_strength': 6.393237174912083e-06, 'bagging_temperature': 0.650201692371258, 'border_count': 138, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.18485433503209892}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,368] Trial 118 finished with value: 0.9364356107660455 and parameters: {'iterations': 500, 'depth': 13, 'learning_rate': 0.03673691330874392, 'l2_leaf_reg': 0.2799205983076537, 'random_strength': 0.0016616549946443778, 'bagging_temperature': 1.1434304755513767, 'border_count': 93, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 92, 'rsm': 0.303980336947833}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,563] Trial 119 finished with value: 0.9360683747634487 and parameters: {'iterations': 355, 'depth': 10, 'learning_rate': 0.026192218124677005, 'l2_leaf_reg': 5.2505961187717196e-08, 'random_strength': 0.04057701767400652, 'bagging_temperature': 0.28706061899925556, 'border_count': 32, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 42, 'rsm': 0.4499415775570732}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,752] Trial 120 finished with value: 0.9420281633568404 and parameters: {'iterations': 373, 'depth': 5, 'learning_rate': 0.04446704544563856, 'l2_leaf_reg': 0.4538460139184795, 'random_strength': 3.1111899899088475e-05, 'bagging_temperature': 0.2425486475025021, 'border_count': 246, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.22838517640724643}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:53,959] Trial 121 finished with value: 0.9394135383169611 and parameters: {'iterations': 460, 'depth': 11, 'learning_rate': 0.017012275631636556, 'l2_leaf_reg': 2.0171376606739177e-07, 'random_strength': 8.792564636872177e-05, 'bagging_temperature': 2.5981546478630135, 'border_count': 122, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.22013559649923678}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,218] Trial 122 finished with value: 0.9450568845585497 and parameters: {'iterations': 467, 'depth': 11, 'learning_rate': 0.015246093022030375, 'l2_leaf_reg': 0.19032853338636235, 'random_strength': 1.9249302192365374e-06, 'bagging_temperature': 4.7543569468289455, 'border_count': 125, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.2654905501049236}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,412] Trial 123 finished with value: 0.9422759321775974 and parameters: {'iterations': 488, 'depth': 12, 'learning_rate': 0.011621123531896068, 'l2_leaf_reg': 0.037647845056465574, 'random_strength': 5.901004171329165e-05, 'bagging_temperature': 6.224125963475733, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 87, 'rsm': 0.17393984193004308}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,708] Trial 124 finished with value: 0.9392165631469979 and parameters: {'iterations': 452, 'depth': 10, 'learning_rate': 0.020963152184374403, 'l2_leaf_reg': 0.0006243147662467919, 'random_strength': 0.0002131427399944794, 'bagging_temperature': 7.743944404779233, 'border_count': 220, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.32484174711862224}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:54,964] Trial 125 finished with value: 0.9366325859360087 and parameters: {'iterations': 476, 'depth': 11, 'learning_rate': 0.010412369273060383, 'l2_leaf_reg': 0.00628453086497708, 'random_strength': 1.0694728932114263e-06, 'bagging_temperature': 0.5377842172748432, 'border_count': 208, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 85, 'rsm': 0.20046815277795216}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:55,238] Trial 126 finished with value: 0.9479394242410895 and parameters: {'iterations': 459, 'depth': 12, 'learning_rate': 0.027921560248912368, 'l2_leaf_reg': 0.0011197201303974583, 'random_strength': 3.7150832167032144e-05, 'bagging_temperature': 0.33772312759685646, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 73, 'rsm': 0.27829439379604715}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:55,459] Trial 127 finished with value: 0.9478823107512284 and parameters: {'iterations': 416, 'depth': 12, 'learning_rate': 0.02695493912678957, 'l2_leaf_reg': 0.000363754132668095, 'random_strength': 1.6953469751716863e-05, 'bagging_temperature': 0.42078596928585504, 'border_count': 130, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.33967599922122954}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:55,763] Trial 128 finished with value: 0.9420991028295376 and parameters: {'iterations': 414, 'depth': 13, 'learning_rate': 0.030581915215354923, 'l2_leaf_reg': 1.9892774757125386e-05, 'random_strength': 1.9636675912559615e-05, 'bagging_temperature': 0.3441681809788324, 'border_count': 135, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.3535543107245493}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:56,117] Trial 129 finished with value: 0.9393918946301925 and parameters: {'iterations': 432, 'depth': 12, 'learning_rate': 0.028629067859029782, 'l2_leaf_reg': 0.00029759590926787367, 'random_strength': 3.816540308358045e-05, 'bagging_temperature': 0.4304419133130016, 'border_count': 131, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 39, 'rsm': 0.2823066601473922}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:56,471] Trial 130 finished with value: 0.9448319458627505 and parameters: {'iterations': 425, 'depth': 12, 'learning_rate': 0.035334699668356964, 'l2_leaf_reg': 0.002309612414548722, 'random_strength': 9.50603405581896e-06, 'bagging_temperature': 0.1921181189333905, 'border_count': 150, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 55, 'rsm': 0.3421712325642315}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:56,716] Trial 131 finished with value: 0.9365180744718671 and parameters: {'iterations': 463, 'depth': 13, 'learning_rate': 0.2502100961097631, 'l2_leaf_reg': 0.0009007701989759662, 'random_strength': 2.773833098122904e-05, 'bagging_temperature': 0.31330238318056797, 'border_count': 114, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.31829183987372855}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,324] Trial 132 finished with value: 0.9136990147276919 and parameters: {'iterations': 442, 'depth': 11, 'learning_rate': 0.024348095854665255, 'l2_leaf_reg': 0.001264909323666646, 'random_strength': 3.150676241429889e-06, 'bagging_temperature': 0.46186652674322926, 'border_count': 143, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 72, 'rsm': 0.8682699354405292}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,517] Trial 133 finished with value: 0.9421995038264234 and parameters: {'iterations': 401, 'depth': 12, 'learning_rate': 0.019311103012232354, 'l2_leaf_reg': 0.0019184237342172986, 'random_strength': 0.00010217748102388497, 'bagging_temperature': 0.3695318985236949, 'border_count': 97, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.30183511209079117}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,730] Trial 134 finished with value: 0.9423051115089043 and parameters: {'iterations': 489, 'depth': 12, 'learning_rate': 0.02774464488294973, 'l2_leaf_reg': 0.00040945750063480554, 'random_strength': 1.576337834706906e-05, 'bagging_temperature': 0.5123293943299259, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 93, 'rsm': 0.25543055128232267}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:57,893] Trial 135 finished with value: 0.9391606495664544 and parameters: {'iterations': 475, 'depth': 13, 'learning_rate': 0.02363710203132887, 'l2_leaf_reg': 5.247097796502152e-07, 'random_strength': 1.0426043429706933e-05, 'bagging_temperature': 0.6091999487797312, 'border_count': 127, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 78, 'rsm': 0.10114604580153895}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,115] Trial 136 finished with value: 0.9450707105413858 and parameters: {'iterations': 387, 'depth': 11, 'learning_rate': 0.05275588992091221, 'l2_leaf_reg': 8.421747261566226e-05, 'random_strength': 0.000141431813427501, 'bagging_temperature': 0.40818391430649775, 'border_count': 109, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.5305909051010704}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,254] Trial 137 finished with value: 0.9422681144736649 and parameters: {'iterations': 388, 'depth': 2, 'learning_rate': 0.054322930763598634, 'l2_leaf_reg': 0.0001949978469938516, 'random_strength': 0.0004333104292700143, 'bagging_temperature': 0.2731806983293307, 'border_count': 103, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 100, 'rsm': 0.498687781787593}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,643] Trial 138 finished with value: 0.9390825456894836 and parameters: {'iterations': 347, 'depth': 11, 'learning_rate': 0.040161823283521164, 'l2_leaf_reg': 0.0006602824581046081, 'random_strength': 0.00017097152095899896, 'bagging_temperature': 0.41607380714001674, 'border_count': 136, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 49, 'rsm': 0.5270340614503363}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:58,926] Trial 139 finished with value: 0.9337256816021439 and parameters: {'iterations': 401, 'depth': 14, 'learning_rate': 0.06628587940533412, 'l2_leaf_reg': 1.153850186992474e-05, 'random_strength': 1.0189969346701975e-07, 'bagging_temperature': 0.8727787081175186, 'border_count': 131, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.5621517728185998}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:59,487] Trial 140 finished with value: 0.9309817335506512 and parameters: {'iterations': 447, 'depth': 12, 'learning_rate': 0.04873334111963402, 'l2_leaf_reg': 0.9943938630341599, 'random_strength': 0.016694319781494524, 'bagging_temperature': 0.3512913463453787, 'border_count': 60, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 12, 'rsm': 0.47806253504933655}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:16:59,771] Trial 141 finished with value: 0.9449308488612835 and parameters: {'iterations': 410, 'depth': 11, 'learning_rate': 0.09080696553566514, 'l2_leaf_reg': 9.823038775267924e-05, 'random_strength': 6.939854564405356e-05, 'bagging_temperature': 0.4616531938747425, 'border_count': 108, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 97, 'rsm': 0.6087092617769291}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,004] Trial 142 finished with value: 0.9392165631469979 and parameters: {'iterations': 383, 'depth': 11, 'learning_rate': 0.03210113857890355, 'l2_leaf_reg': 0.0026887421482416993, 'random_strength': 3.765884321811762e-05, 'bagging_temperature': 0.4118834611950506, 'border_count': 115, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 24, 'rsm': 0.13535857801156687}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,287] Trial 143 finished with value: 0.9420419893396765 and parameters: {'iterations': 432, 'depth': 10, 'learning_rate': 0.038798992992227554, 'l2_leaf_reg': 0.0034741180567567412, 'random_strength': 0.0002713146202368732, 'bagging_temperature': 1.8012944200478604, 'border_count': 110, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.5400120064708985}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,628] Trial 144 finished with value: 0.942245284348707 and parameters: {'iterations': 418, 'depth': 11, 'learning_rate': 0.0791067496320934, 'l2_leaf_reg': 2.0789296632826364, 'random_strength': 0.00012954682210043842, 'bagging_temperature': 0.29682505882415755, 'border_count': 124, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 75, 'rsm': 0.46616896879851744}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:00,977] Trial 145 finished with value: 0.9307339647298944 and parameters: {'iterations': 456, 'depth': 12, 'learning_rate': 0.057708055393875246, 'l2_leaf_reg': 1.344858568035081e-06, 'random_strength': 4.540543632281483e-06, 'bagging_temperature': 0.5584292910538805, 'border_count': 101, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 90, 'rsm': 0.6415174624180923}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:01,154] Trial 146 finished with value: 0.9391606495664544 and parameters: {'iterations': 483, 'depth': 10, 'learning_rate': 0.044217578258479565, 'l2_leaf_reg': 0.0011889679366554329, 'random_strength': 1.464865467543225, 'bagging_temperature': 0.32672860462852166, 'border_count': 83, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 99, 'rsm': 0.26647106843219254}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:01,475] Trial 147 finished with value: 0.9364356107660455 and parameters: {'iterations': 468, 'depth': 12, 'learning_rate': 0.021464305942117096, 'l2_leaf_reg': 0.009334993746607368, 'random_strength': 0.000668552265044122, 'bagging_temperature': 8.862006303293871, 'border_count': 116, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.5154318707930476}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:01,820] Trial 148 finished with value: 0.942245284348707 and parameters: {'iterations': 494, 'depth': 13, 'learning_rate': 0.013240135648172328, 'l2_leaf_reg': 9.256222542785185e-08, 'random_strength': 0.004389309226115299, 'bagging_temperature': 0.3810188561669928, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 68, 'rsm': 0.2905578012712258}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:02,182] Trial 149 finished with value: 0.9420419893396765 and parameters: {'iterations': 442, 'depth': 12, 'learning_rate': 0.026276610480490587, 'l2_leaf_reg': 0.018184055160189394, 'random_strength': 0.001160278323404396, 'bagging_temperature': 0.4994469700760825, 'border_count': 129, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 92, 'rsm': 0.5892674146326472}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:02,932] Trial 150 finished with value: 0.9393576247364175 and parameters: {'iterations': 479, 'depth': 11, 'learning_rate': 0.017909665495729164, 'l2_leaf_reg': 3.418791190835952e-08, 'random_strength': 4.9316581417474394e-05, 'bagging_temperature': 0.2581840409523552, 'border_count': 105, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 6, 'rsm': 0.33059365320417256}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,120] Trial 151 finished with value: 0.9392165631469979 and parameters: {'iterations': 460, 'depth': 11, 'learning_rate': 0.015844361923020113, 'l2_leaf_reg': 0.06242436487813967, 'random_strength': 2.7294282776467616e-05, 'bagging_temperature': 2.237567853852061, 'border_count': 117, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 80, 'rsm': 0.15432115118896458}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,275] Trial 152 finished with value: 0.9420281633568404 and parameters: {'iterations': 307, 'depth': 10, 'learning_rate': 0.03513004502618466, 'l2_leaf_reg': 0.10677773168166566, 'random_strength': 7.12467611021974e-05, 'bagging_temperature': 3.4000812647715395, 'border_count': 123, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 83, 'rsm': 0.21908078522196517}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,556] Trial 153 finished with value: 0.9422897581604335 and parameters: {'iterations': 454, 'depth': 11, 'learning_rate': 0.01736942289114766, 'l2_leaf_reg': 0.6057033139880593, 'random_strength': 1.662852062105787e-05, 'bagging_temperature': 5.1533816618993225, 'border_count': 240, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.2500286572700599}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:03,804] Trial 154 finished with value: 0.9392165631469979 and parameters: {'iterations': 470, 'depth': 11, 'learning_rate': 0.02180369139093789, 'l2_leaf_reg': 5.365532742813126e-06, 'random_strength': 4.764746563966035e-05, 'bagging_temperature': 6.962252063321166, 'border_count': 250, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.24164552701504163}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,055] Trial 155 finished with value: 0.9420281633568404 and parameters: {'iterations': 437, 'depth': 12, 'learning_rate': 0.014025048100410055, 'l2_leaf_reg': 0.02942261064762721, 'random_strength': 0.00012661997678511193, 'bagging_temperature': 1.428644549746044, 'border_count': 143, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 61, 'rsm': 0.19733653394586823}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,343] Trial 156 finished with value: 0.9424733829640397 and parameters: {'iterations': 424, 'depth': 15, 'learning_rate': 0.027584687851370693, 'l2_leaf_reg': 0.29289799744567774, 'random_strength': 0.00029810253532579494, 'bagging_temperature': 0.5910808047715936, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 89, 'rsm': 0.3649935157963945}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,567] Trial 157 finished with value: 0.9422897581604335 and parameters: {'iterations': 500, 'depth': 8, 'learning_rate': 0.00901702182872297, 'l2_leaf_reg': 3.225175618190725e-05, 'random_strength': 5.9851862067132196e-06, 'bagging_temperature': 9.908711348745099, 'border_count': 148, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 94, 'rsm': 0.2299046581579018}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:04,896] Trial 158 finished with value: 0.9392330734328883 and parameters: {'iterations': 462, 'depth': 13, 'learning_rate': 0.0013935426903720562, 'l2_leaf_reg': 0.14008351382588624, 'random_strength': 2.369260775666672e-05, 'bagging_temperature': 0.4395591771328395, 'border_count': 133, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 74, 'rsm': 0.27863519108727014}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:06,065] Trial 159 finished with value: 0.9301439811851072 and parameters: {'iterations': 155, 'depth': 9, 'learning_rate': 0.019097821061106832, 'l2_leaf_reg': 0.006194130972191863, 'random_strength': 1.4295326838866243e-05, 'bagging_temperature': 0.6814306150232909, 'border_count': 163, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 65, 'rsm': 0.43586584061754363}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:07,160] Trial 160 finished with value: 0.9420218435177732 and parameters: {'iterations': 488, 'depth': 10, 'learning_rate': 0.032756415738802266, 'l2_leaf_reg': 0.0008852235114852314, 'random_strength': 8.600949207782079e-05, 'bagging_temperature': 0.5373270810790087, 'border_count': 111, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 52, 'rsm': 0.4917947838104507}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:07,537] Trial 161 finished with value: 0.9419079718821625 and parameters: {'iterations': 446, 'depth': 4, 'learning_rate': 0.015539514333519456, 'l2_leaf_reg': 4.889776520122877, 'random_strength': 0.0009313366488436875, 'bagging_temperature': 0.3672581246244092, 'border_count': 155, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 2, 'rsm': 0.2673764128336307}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:08,380] Trial 162 finished with value: 0.9448535895495193 and parameters: {'iterations': 475, 'depth': 3, 'learning_rate': 0.021850054135842855, 'l2_leaf_reg': 0.07511660282185649, 'random_strength': 0.0020123581833509357, 'bagging_temperature': 0.344424780392622, 'border_count': 127, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 78, 'rsm': 0.2089112701899995}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,247] Trial 163 finished with value: 0.9450568845585497 and parameters: {'iterations': 320, 'depth': 4, 'learning_rate': 0.025276377314971288, 'l2_leaf_reg': 0.1775039781494037, 'random_strength': 5.901525276899961e-07, 'bagging_temperature': 0.47513410689487956, 'border_count': 145, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 45, 'rsm': 0.3056672204395963}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,396] Trial 164 finished with value: 0.9420281633568404 and parameters: {'iterations': 451, 'depth': 3, 'learning_rate': 0.017027809049485573, 'l2_leaf_reg': 0.8431126650682025, 'random_strength': 0.006265987027362102, 'bagging_temperature': 0.3287967201175384, 'border_count': 140, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 96, 'rsm': 0.18023769816221066}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,660] Trial 165 finished with value: 0.9391964173250944 and parameters: {'iterations': 441, 'depth': 5, 'learning_rate': 0.019654004388037327, 'l2_leaf_reg': 2.962806671659982, 'random_strength': 0.00046456659205713837, 'bagging_temperature': 0.41793940274356656, 'border_count': 136, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 20, 'rsm': 0.2491760323144459}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:09,841] Trial 166 finished with value: 0.9420281633568404 and parameters: {'iterations': 431, 'depth': 12, 'learning_rate': 0.04825961750253769, 'l2_leaf_reg': 0.3864623653407632, 'random_strength': 0.0002106851591803803, 'bagging_temperature': 0.30726417093872255, 'border_count': 95, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 76, 'rsm': 0.12462026159271422}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:10,749] Trial 167 finished with value: 0.9364292909269782 and parameters: {'iterations': 464, 'depth': 11, 'learning_rate': 0.028930996110599103, 'l2_leaf_reg': 0.04410691026043362, 'random_strength': 0.0011414873923234618, 'bagging_temperature': 0.3772427474271183, 'border_count': 150, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 25, 'rsm': 0.5470029379168437}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,025] Trial 168 finished with value: 0.9392165631469979 and parameters: {'iterations': 483, 'depth': 7, 'learning_rate': 0.023530434704186497, 'l2_leaf_reg': 0.00043497423339023495, 'random_strength': 3.700167074678586e-05, 'bagging_temperature': 0.6287303886622022, 'border_count': 178, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 82, 'rsm': 0.2872040142291833}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,352] Trial 169 finished with value: 0.9391606495664544 and parameters: {'iterations': 419, 'depth': 11, 'learning_rate': 0.011066677702838626, 'l2_leaf_reg': 3.3218560135089747e-07, 'random_strength': 6.273259312642815e-05, 'bagging_temperature': 0.47382001617043684, 'border_count': 90, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 14, 'rsm': 0.1503567953926859}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,502] Trial 170 finished with value: 0.9420281633568404 and parameters: {'iterations': 410, 'depth': 4, 'learning_rate': 0.06752711692568371, 'l2_leaf_reg': 0.001710704283225401, 'random_strength': 7.762246146156258e-06, 'bagging_temperature': 7.677579394294883, 'border_count': 106, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 69, 'rsm': 0.22951185589278955}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,668] Trial 171 finished with value: 0.939247210975888 and parameters: {'iterations': 500, 'depth': 11, 'learning_rate': 0.02000585732933726, 'l2_leaf_reg': 0.0006763625137768598, 'random_strength': 0.0005407013316711388, 'bagging_temperature': 0.5340715524087578, 'border_count': 101, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 100, 'rsm': 0.16311940628182714}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:11,837] Trial 172 finished with value: 0.9420281633568404 and parameters: {'iterations': 492, 'depth': 5, 'learning_rate': 0.014896680959692137, 'l2_leaf_reg': 1.4385889711686615, 'random_strength': 0.0007178660770454293, 'bagging_temperature': 0.7563960208234407, 'border_count': 111, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 86, 'rsm': 0.17243296476590866}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,000] Trial 173 finished with value: 0.9450568845585497 and parameters: {'iterations': 473, 'depth': 5, 'learning_rate': 0.023027426925292, 'l2_leaf_reg': 0.0002781682518945414, 'random_strength': 0.00010782305847558164, 'bagging_temperature': 0.5867396501064782, 'border_count': 99, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 84, 'rsm': 0.19470730255701207}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,235] Trial 174 finished with value: 0.939377770558321 and parameters: {'iterations': 482, 'depth': 4, 'learning_rate': 0.03241964888238338, 'l2_leaf_reg': 0.0003457154290776943, 'random_strength': 0.00044451681264570474, 'bagging_temperature': 0.4432670512593227, 'border_count': 233, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 80, 'rsm': 0.26332909539982013}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,533] Trial 175 finished with value: 0.9394832914849566 and parameters: {'iterations': 457, 'depth': 13, 'learning_rate': 0.04045814491944505, 'l2_leaf_reg': 0.0001402936281707434, 'random_strength': 0.0001840161471214937, 'bagging_temperature': 0.5079765193842785, 'border_count': 213, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 87, 'rsm': 0.3167030107845214}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:12,760] Trial 176 finished with value: 0.9420281633568404 and parameters: {'iterations': 493, 'depth': 4, 'learning_rate': 0.027519881479168753, 'l2_leaf_reg': 0.004053512628934247, 'random_strength': 0.0003219786489434715, 'bagging_temperature': 0.41135083844257087, 'border_count': 185, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 92, 'rsm': 0.34090137490760997}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,115] Trial 177 finished with value: 0.9478701466895731 and parameters: {'iterations': 294, 'depth': 14, 'learning_rate': 0.017432667951942236, 'l2_leaf_reg': 8.069010518000647e-05, 'random_strength': 0.10401852426690426, 'bagging_temperature': 0.22484682170681464, 'border_count': 203, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 98, 'rsm': 0.5766975974859562}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,395] Trial 178 finished with value: 0.9423087176776352 and parameters: {'iterations': 265, 'depth': 14, 'learning_rate': 0.01247518250258224, 'l2_leaf_reg': 0.0002203658912485584, 'random_strength': 0.1334227737202125, 'bagging_temperature': 0.2670035665869987, 'border_count': 196, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 98, 'rsm': 0.5318296390483455}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,644] Trial 179 finished with value: 0.9448535895495193 and parameters: {'iterations': 238, 'depth': 14, 'learning_rate': 0.01807673012308473, 'l2_leaf_reg': 0.01399085651991093, 'random_strength': 0.2960932676404893, 'bagging_temperature': 0.15351918050488025, 'border_count': 255, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 96, 'rsm': 0.5114009411786454}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:13,998] Trial 180 finished with value: 0.9449107030393801 and parameters: {'iterations': 450, 'depth': 14, 'learning_rate': 0.03589837606023441, 'l2_leaf_reg': 6.662649961466868e-05, 'random_strength': 0.07909578018195974, 'bagging_temperature': 0.23722827797048798, 'border_count': 132, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 71, 'rsm': 0.2793912618414582}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:14,157] Trial 181 finished with value: 0.9422031967509996 and parameters: {'iterations': 282, 'depth': 3, 'learning_rate': 0.020907669083619945, 'l2_leaf_reg': 4.0417023367134544e-05, 'random_strength': 0.0029292950598705124, 'bagging_temperature': 0.2048019984702627, 'border_count': 114, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 98, 'rsm': 0.5726568945580828}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:14,532] Trial 182 finished with value: 0.9308692175907287 and parameters: {'iterations': 300, 'depth': 16, 'learning_rate': 0.016977587931415225, 'l2_leaf_reg': 6.428861894888382e-05, 'random_strength': 4.481525163941594e-05, 'bagging_temperature': 0.2915045702805398, 'border_count': 202, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 94, 'rsm': 0.5886491339618192}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:14,761] Trial 183 finished with value: 0.9394769716458893 and parameters: {'iterations': 221, 'depth': 12, 'learning_rate': 0.024351404002375798, 'l2_leaf_reg': 0.000571971133855846, 'random_strength': 2.4460781047220314e-05, 'bagging_temperature': 0.22238886441296601, 'border_count': 172, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 100, 'rsm': 0.5577041652720683}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:15,345] Trial 184 finished with value: 0.9478606670644598 and parameters: {'iterations': 374, 'depth': 10, 'learning_rate': 0.018862089757160656, 'l2_leaf_reg': 0.0002711773955536017, 'random_strength': 0.00013899680340439353, 'bagging_temperature': 4.376392538372629, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 10, 'rsm': 0.21282910430945437}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:15,933] Trial 185 finished with value: 0.9422251385268036 and parameters: {'iterations': 373, 'depth': 10, 'learning_rate': 0.01341908033642766, 'l2_leaf_reg': 1.3301485751827285e-07, 'random_strength': 8.258702096105676e-05, 'bagging_temperature': 6.313550576053137, 'border_count': 125, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 8, 'rsm': 0.21582168224439763}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:16,955] Trial 186 finished with value: 0.9366461056733522 and parameters: {'iterations': 354, 'depth': 11, 'learning_rate': 0.016015514757403242, 'l2_leaf_reg': 0.0012157604267309754, 'random_strength': 0.00014286883311715454, 'bagging_temperature': 3.8355646079201944, 'border_count': 120, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 4, 'rsm': 0.24455713560531547}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:18,240] Trial 187 finished with value: 0.9393714507192537 and parameters: {'iterations': 387, 'depth': 9, 'learning_rate': 0.029773522710607077, 'l2_leaf_reg': 0.18964502202298492, 'random_strength': 0.05665749832122518, 'bagging_temperature': 4.316804556211732, 'border_count': 224, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 5, 'rsm': 0.29112694915279064}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:19,109] Trial 188 finished with value: 0.9365246787953542 and parameters: {'iterations': 328, 'depth': 10, 'learning_rate': 0.019103470294199343, 'l2_leaf_reg': 6.562015740609845, 'random_strength': 0.030892780955495254, 'bagging_temperature': 5.561691546696606, 'border_count': 129, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 10, 'rsm': 0.6181631034200274}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:20,111] Trial 189 finished with value: 0.9364154649441421 and parameters: {'iterations': 363, 'depth': 12, 'learning_rate': 0.014354312995037964, 'l2_leaf_reg': 0.0881351634444277, 'random_strength': 1.973507344724729e-06, 'bagging_temperature': 8.141642491918113, 'border_count': 137, 'grow_policy': 'Depthwise', 'min_data_in_leaf': 16, 'rsm': 0.19449893094423057}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:49,051] Trial 190 finished with value: 0.9326620320519092 and parameters: {'iterations': 394, 'depth': 13, 'learning_rate': 0.02538912391774518, 'l2_leaf_reg': 0.0024456588938525075, 'random_strength': 0.09893594885717653, 'bagging_temperature': 2.6586561536924234, 'border_count': 119, 'grow_policy': 'SymmetricTree', 'min_data_in_leaf': 97, 'rsm': 0.4961944560276764}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:50,393] Trial 191 finished with value: 0.9364356107660455 and parameters: {'iterations': 377, 'depth': 15, 'learning_rate': 0.02160748607378081, 'l2_leaf_reg': 0.00018784167765087707, 'random_strength': 5.661101716609462e-05, 'bagging_temperature': 0.5520159277072044, 'border_count': 105, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 33, 'rsm': 0.13638530175267316}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:51,336] Trial 192 finished with value: 0.9365766723554652 and parameters: {'iterations': 345, 'depth': 11, 'learning_rate': 0.018153545563738348, 'l2_leaf_reg': 0.0002689381199903756, 'random_strength': 0.0013202072873539827, 'bagging_temperature': 3.05875393809237, 'border_count': 108, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 47, 'rsm': 0.1833083713837859}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:52,234] Trial 193 finished with value: 0.9422759321775974 and parameters: {'iterations': 472, 'depth': 11, 'learning_rate': 0.01967261015798756, 'l2_leaf_reg': 0.00010269003059595126, 'random_strength': 0.0003224919649464639, 'bagging_temperature': 4.7403514956391515, 'border_count': 114, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 95, 'rsm': 0.22203325266748072}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:52,590] Trial 194 finished with value: 0.9450707105413858 and parameters: {'iterations': 479, 'depth': 12, 'learning_rate': 0.022953910052071345, 'l2_leaf_reg': 0.00033355714664964474, 'random_strength': 0.00021059453778553297, 'bagging_temperature': 0.3911695421583786, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.53058333271746}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:52,915] Trial 195 finished with value: 0.9479595700629927 and parameters: {'iterations': 468, 'depth': 12, 'learning_rate': 0.027646391674950158, 'l2_leaf_reg': 0.0008940375907121934, 'random_strength': 0.00017370575325460964, 'bagging_temperature': 0.17637761154801543, 'border_count': 123, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 92, 'rsm': 0.5383588788987733}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:53,243] Trial 196 finished with value: 0.9448749352807401 and parameters: {'iterations': 466, 'depth': 12, 'learning_rate': 0.031699768142828835, 'l2_leaf_reg': 0.0010108484321680307, 'random_strength': 0.00015777611403595265, 'bagging_temperature': 0.14876062009712754, 'border_count': 126, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 91, 'rsm': 0.5254795998656782}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:53,584] Trial 197 finished with value: 0.9334006901311248 and parameters: {'iterations': 482, 'depth': 12, 'learning_rate': 0.026842474376006505, 'l2_leaf_reg': 0.0006848580407660518, 'random_strength': 0.00010498978622202728, 'bagging_temperature': 0.18830195664870608, 'border_count': 124, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 94, 'rsm': 0.5497198397999028}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:53,820] Trial 198 finished with value: 0.9420419893396765 and parameters: {'iterations': 295, 'depth': 12, 'learning_rate': 0.03677738161683119, 'l2_leaf_reg': 0.00036343825894797515, 'random_strength': 0.0002479113992623705, 'bagging_temperature': 0.14005757368990798, 'border_count': 122, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 89, 'rsm': 0.5391037144265599}. Best is trial 99 with value: 0.948099087498995.\n", + "[I 2025-08-17 19:17:54,203] Trial 199 finished with value: 0.9450707105413858 and parameters: {'iterations': 460, 'depth': 12, 'learning_rate': 0.04545859371569691, 'l2_leaf_reg': 0.0016986307026388967, 'random_strength': 3.772429639477264e-05, 'bagging_temperature': 0.1322329379931608, 'border_count': 128, 'grow_policy': 'Lossguide', 'min_data_in_leaf': 97, 'rsm': 0.5717542930999647}. Best is trial 99 with value: 0.948099087498995.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best trial:\n", + "F1 Score: 0.948099\n", + "Parameters:\n", + "iterations: 478\n", + "depth: 12\n", + "learning_rate: 0.04254101358886379\n", + "l2_leaf_reg: 1.7277473564532868e-07\n", + "random_strength: 0.0019440779833289569\n", + "bagging_temperature: 0.5084286556246295\n", + "border_count: 140\n", + "grow_policy: Depthwise\n", + "min_data_in_leaf: 7\n", + "rsm: 0.37971137763889\n" + ] + } + ], + "source": [ + "from catboost import CatBoostClassifier\n", + "\n", + "\n", + "def objective(trial):\n", + " params = {\n", + " \"iterations\": trial.suggest_int(\"iterations\", 50, 500),\n", + " \"depth\": trial.suggest_int(\"depth\", 1, 16),\n", + " \"learning_rate\": trial.suggest_float(\"learning_rate\", 1e-3, 0.5, log=True),\n", + " \"l2_leaf_reg\": trial.suggest_float(\"l2_leaf_reg\", 1e-8, 10.0, log=True),\n", + " \"random_strength\": trial.suggest_float(\"random_strength\", 1e-8, 10.0, log=True),\n", + " \"bagging_temperature\": trial.suggest_float(\n", + " \"bagging_temperature\", 0.1, 10.0, log=True\n", + " ),\n", + " \"border_count\": trial.suggest_int(\"border_count\", 32, 255),\n", + " \"grow_policy\": trial.suggest_categorical(\n", + " \"grow_policy\", [\"SymmetricTree\", \"Depthwise\", \"Lossguide\"]\n", + " ),\n", + " \"min_data_in_leaf\": trial.suggest_int(\"min_data_in_leaf\", 1, 100),\n", + " \"rsm\": trial.suggest_float(\"rsm\", 0.1, 1.0),\n", + " \"loss_function\": \"Logloss\",\n", + " \"eval_metric\": \"F1\",\n", + " \"cat_features\": categorical_cols,\n", + " \"verbose\": 0,\n", + " }\n", + "\n", + " model = CatBoostClassifier(**params)\n", + "\n", + " scores = cross_val_score(\n", + " estimator=model,\n", + " X=X,\n", + " y=y,\n", + " scoring=\"f1_weighted\",\n", + " cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=42),\n", + " n_jobs=-1,\n", + " )\n", + "\n", + " return scores.mean()\n", + "\n", + "\n", + "study = optuna.create_study(direction=\"maximize\")\n", + "study.optimize(objective, n_trials=200)\n", + "\n", + "best_trial = study.best_trial\n", + "\n", + "print(\"Best trial:\")\n", + "print(f\"F1 Score: {best_trial.value:.6f}\")\n", + "print(\"Parameters:\")\n", + "for k, v in best_trial.params.items():\n", + " print(f\"{k}: {v}\")" + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 25.7k/25.7k [00:00<00:00, 504kB/s]\n" - ] + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/var/folders/dj/6m_rn6_56pvb0zb7k0t6bz4r0000gn/T/ipykernel_1127/3819207535.py:8: DeprecationWarning: Use dataset_load() instead of load_dataset(). load_dataset() will be removed in a future version.\n", + " df = kagglehub.load_dataset(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading from https://www.kaggle.com/api/v1/datasets/download/bhavikjikadara/loan-status-prediction?dataset_version_number=1&file_name=loan_data.csv...\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "100%|██████████| 25.7k/25.7k [00:00<00:00, 504kB/s]\n" + ] + }, + { + "data": { + "text/html": [ + "
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Loan_IDGenderMarriedDependentsEducationSelf_EmployedApplicantIncomeCoapplicantIncomeLoanAmountLoan_Amount_TermCredit_HistoryProperty_AreaLoan_Status
0LP001003MaleYes1GraduateNo45831508.0128.0360.01.0RuralN
1LP001005MaleYes0GraduateYes30000.066.0360.01.0UrbanY
2LP001006MaleYes0Not GraduateNo25832358.0120.0360.01.0UrbanY
3LP001008MaleNo0GraduateNo60000.0141.0360.01.0UrbanY
4LP001013MaleYes0Not GraduateNo23331516.095.0360.01.0UrbanY
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376LP002953MaleYes3+GraduateNo57030.0128.0360.01.0UrbanY
377LP002974MaleYes0GraduateNo32321950.0108.0360.01.0RuralY
378LP002978FemaleNo0GraduateNo29000.071.0360.01.0RuralY
379LP002979MaleYes3+GraduateNo41060.040.0180.01.0RuralY
380LP002990FemaleNo0GraduateYes45830.0133.0360.00.0SemiurbanN
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" + ], + "text/plain": [ + " Loan_ID Gender Married Dependents Education Self_Employed \\\n", + "0 LP001003 Male Yes 1 Graduate No \n", + "1 LP001005 Male Yes 0 Graduate Yes \n", + "2 LP001006 Male Yes 0 Not Graduate No \n", + "3 LP001008 Male No 0 Graduate No \n", + "4 LP001013 Male Yes 0 Not Graduate No \n", + ".. ... ... ... ... ... ... \n", + "376 LP002953 Male Yes 3+ Graduate No \n", + "377 LP002974 Male Yes 0 Graduate No \n", + "378 LP002978 Female No 0 Graduate No \n", + "379 LP002979 Male Yes 3+ Graduate No \n", + "380 LP002990 Female No 0 Graduate Yes \n", + "\n", + " ApplicantIncome CoapplicantIncome LoanAmount Loan_Amount_Term \\\n", + "0 4583 1508.0 128.0 360.0 \n", + "1 3000 0.0 66.0 360.0 \n", + "2 2583 2358.0 120.0 360.0 \n", + "3 6000 0.0 141.0 360.0 \n", + "4 2333 1516.0 95.0 360.0 \n", + ".. ... ... ... ... \n", + "376 5703 0.0 128.0 360.0 \n", + "377 3232 1950.0 108.0 360.0 \n", + "378 2900 0.0 71.0 360.0 \n", + "379 4106 0.0 40.0 180.0 \n", + "380 4583 0.0 133.0 360.0 \n", + "\n", + " Credit_History Property_Area Loan_Status \n", + "0 1.0 Rural N \n", + "1 1.0 Urban Y \n", + "2 1.0 Urban Y \n", + "3 1.0 Urban Y \n", + "4 1.0 Urban Y \n", + ".. ... ... ... \n", + "376 1.0 Urban Y \n", + "377 1.0 Rural Y \n", + "378 1.0 Rural Y \n", + "379 1.0 Rural Y \n", + "380 0.0 Semiurban N \n", + "\n", + "[381 rows x 13 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import kagglehub\n", + "from kagglehub import KaggleDatasetAdapter\n", + "\n", + "# Set the path to the file you'd like to load\n", + "file_path = \"loan_data.csv\"\n", + "\n", + "# Load the latest version\n", + "df = kagglehub.load_dataset(\n", + " KaggleDatasetAdapter.PANDAS,\n", + " \"\",\n", + " file_path,\n", + ")\n", + "\n", + "df" + ] }, { - "data": { - "text/html": [ - "
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Loan_IDGenderMarriedDependentsEducationSelf_EmployedApplicantIncomeCoapplicantIncomeLoanAmountLoan_Amount_TermCredit_HistoryProperty_AreaLoan_Status
0LP001003MaleYes1GraduateNo45831508.0128.0360.01.0RuralN
1LP001005MaleYes0GraduateYes30000.066.0360.01.0UrbanY
2LP001006MaleYes0Not GraduateNo25832358.0120.0360.01.0UrbanY
3LP001008MaleNo0GraduateNo60000.0141.0360.01.0UrbanY
4LP001013MaleYes0Not GraduateNo23331516.095.0360.01.0UrbanY
..........................................
376LP002953MaleYes3+GraduateNo57030.0128.0360.01.0UrbanY
377LP002974MaleYes0GraduateNo32321950.0108.0360.01.0RuralY
378LP002978FemaleNo0GraduateNo29000.071.0360.01.0RuralY
379LP002979MaleYes3+GraduateNo41060.040.0180.01.0RuralY
380LP002990FemaleNo0GraduateYes45830.0133.0360.00.0SemiurbanN
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381 rows × 13 columns

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" + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting kagglehub\n", + " Downloading kagglehub-0.3.13-py3-none-any.whl.metadata (38 kB)\n", + "Requirement already satisfied: packaging in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (25.0)\n", + "Requirement already satisfied: pyyaml in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (6.0.2)\n", + "Requirement already satisfied: requests in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (2.32.4)\n", + "Requirement already satisfied: tqdm in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (4.67.1)\n", + "Requirement already satisfied: charset_normalizer<4,>=2 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (3.4.2)\n", + "Requirement already satisfied: idna<4,>=2.5 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (3.10)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (2.5.0)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (2025.7.14)\n", + "Downloading kagglehub-0.3.13-py3-none-any.whl (68 kB)\n", + "Installing collected packages: kagglehub\n", + "Successfully installed kagglehub-0.3.13\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } ], - "text/plain": [ - " Loan_ID Gender Married Dependents Education Self_Employed \\\n", - "0 LP001003 Male Yes 1 Graduate No \n", - "1 LP001005 Male Yes 0 Graduate Yes \n", - "2 LP001006 Male Yes 0 Not Graduate No \n", - "3 LP001008 Male No 0 Graduate No \n", - "4 LP001013 Male Yes 0 Not Graduate No \n", - ".. ... ... ... ... ... ... \n", - "376 LP002953 Male Yes 3+ Graduate No \n", - "377 LP002974 Male Yes 0 Graduate No \n", - "378 LP002978 Female No 0 Graduate No \n", - "379 LP002979 Male Yes 3+ Graduate No \n", - "380 LP002990 Female No 0 Graduate Yes \n", - "\n", - " ApplicantIncome CoapplicantIncome LoanAmount Loan_Amount_Term \\\n", - "0 4583 1508.0 128.0 360.0 \n", - "1 3000 0.0 66.0 360.0 \n", - "2 2583 2358.0 120.0 360.0 \n", - "3 6000 0.0 141.0 360.0 \n", - "4 2333 1516.0 95.0 360.0 \n", - ".. ... ... ... ... \n", - "376 5703 0.0 128.0 360.0 \n", - "377 3232 1950.0 108.0 360.0 \n", - "378 2900 0.0 71.0 360.0 \n", - "379 4106 0.0 40.0 180.0 \n", - "380 4583 0.0 133.0 360.0 \n", - "\n", - " Credit_History Property_Area Loan_Status \n", - "0 1.0 Rural N \n", - "1 1.0 Urban Y \n", - "2 1.0 Urban Y \n", - "3 1.0 Urban Y \n", - "4 1.0 Urban Y \n", - ".. ... ... ... \n", - "376 1.0 Urban Y \n", - "377 1.0 Rural Y \n", - "378 1.0 Rural Y \n", - "379 1.0 Rural Y \n", - "380 0.0 Semiurban N \n", - "\n", - "[381 rows x 13 columns]" + "source": [ + "pip install kagglehub" ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" } - ], - "source": [ - "import kagglehub\n", - "from kagglehub import KaggleDatasetAdapter\n", - "\n", - "# Set the path to the file you'd like to load\n", - "file_path = \"loan_data.csv\"\n", - "\n", - "# Load the latest version\n", - "df = kagglehub.load_dataset(\n", - " KaggleDatasetAdapter.PANDAS,\n", - " \"\",\n", - " file_path,\n", - ")\n", - "\n", - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting kagglehub\n", - " Downloading kagglehub-0.3.13-py3-none-any.whl.metadata (38 kB)\n", - "Requirement already satisfied: packaging in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (25.0)\n", - "Requirement already satisfied: pyyaml in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (6.0.2)\n", - "Requirement already satisfied: requests in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (2.32.4)\n", - "Requirement already satisfied: tqdm in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from kagglehub) (4.67.1)\n", - "Requirement already satisfied: charset_normalizer<4,>=2 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (3.4.2)\n", - "Requirement already satisfied: idna<4,>=2.5 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (3.10)\n", - "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (2.5.0)\n", - "Requirement already satisfied: certifi>=2017.4.17 in /Users/hamidrezakeshavarz/Documents/GitHub/linearboost-classifier/.venv/lib/python3.13/site-packages (from requests->kagglehub) (2025.7.14)\n", - "Downloading kagglehub-0.3.13-py3-none-any.whl (68 kB)\n", - "Installing collected packages: kagglehub\n", - "Successfully installed kagglehub-0.3.13\n", - "Note: you may need to restart the kernel to use updated packages.\n" - ] + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.13.9)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" } - ], - "source": [ - "pip install kagglehub" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.13.9)", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.9" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } From a49e982934104df0c4d1fffea02c5e4a2bbe05d6 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sat, 7 Mar 2026 16:27:28 +0100 Subject: [PATCH 7/7] Lint corrected --- src/linearboost/linear_boost.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 26b1851..a88c6ba 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -2150,4 +2150,4 @@ def predict_proba(self, X): return self._gradient_predict_proba(test_data) # For AdaBoost, use parent implementation - return super().predict_proba(X) \ No newline at end of file + return super().predict_proba(X)