From 399b419b7734bb4025567c19c1ab880ea9de5e9b Mon Sep 17 00:00:00 2001
From: Elle <elleobrien11@gmail.com>
Date: Thu, 10 Sep 2020 14:02:09 -0700
Subject: [PATCH 1/3] my favorite model

---
 models/model.pkl | Bin 682 -> 724 bytes
 train.py         |   4 ++--
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/models/model.pkl b/models/model.pkl
index b33a4ffb9300be3bd54679b9e6b2955be896b162..b867d0fb1b2e7b277a930e70e61fa478c42151ea 100644
GIT binary patch
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diff --git a/train.py b/train.py
index 2dcb69be..d1bbd7bf 100644
--- a/train.py
+++ b/train.py
@@ -1,12 +1,12 @@
 from sklearn.datasets import make_regression
-from sklearn.linear_model import LinearRegression
+from sklearn.linear_model import Lasso
 import pickle
 import os
 
 X, y = make_regression(10000,n_features = 10)
 
 # Train a model
-reg = LinearRegression().fit(X, y.ravel())
+reg = Lasso().fit(X, y.ravel())
 # Print out training r2
 print(reg.score(X,y.ravel() ))
 

From 3ac2f30f9d479de2525fe580814a0d0539e030e5 Mon Sep 17 00:00:00 2001
From: Elle O'Brien <elleobrien11@gmail.com>
Date: Thu, 10 Sep 2020 14:05:51 -0700
Subject: [PATCH 2/3] Update requirements.txt

---
 requirements.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/requirements.txt b/requirements.txt
index c36e9f95..86b7f277 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,3 +5,4 @@ pytz==2020.1
 scipy==1.5.2
 six==1.15.0
 threadpoolctl==2.1.0
+scikit-learn

From f7609015280d68b12098fce9895493f26a226f96 Mon Sep 17 00:00:00 2001
From: Elle <elleobrien11@gmail.com>
Date: Thu, 10 Sep 2020 14:09:28 -0700
Subject: [PATCH 3/3] fixed # of inputs

---
 models/model.pkl | Bin 724 -> 732 bytes
 train.py         |   2 +-
 2 files changed, 1 insertion(+), 1 deletion(-)

diff --git a/models/model.pkl b/models/model.pkl
index b867d0fb1b2e7b277a930e70e61fa478c42151ea..6c55e7e0020950fd966f249a2cae989c7fdea887 100644
GIT binary patch
delta 135
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diff --git a/train.py b/train.py
index d1bbd7bf..7662da2f 100644
--- a/train.py
+++ b/train.py
@@ -3,7 +3,7 @@
 import pickle
 import os
 
-X, y = make_regression(10000,n_features = 10)
+X, y = make_regression(10000,n_features = 11)
 
 # Train a model
 reg = Lasso().fit(X, y.ravel())