The course introduces the machine learning principles and models, including basic theory of learning.
Abstract: This project tests the effectiveness of multiple Machine Learning models and libraries on a regression task, namely: Decision Tree, Extra Tree, K-Nearest Neighbors, Support Vector Machine, Random Forest, Bagging and MLP. At the end, we implemented an ensemble model with the top five performing models.
Developed by: Veronica Pistolesi, Francesca Poli (lady-de-bugs) 🐞
Academic year: 2022/2023
Master degree: Computer Science, Artificial Intelligence curriculum
This repository contains our final project for the exam, composed of two distinct assignments:
- MONK: classification task using the UCI's MONK problems dataset
- CUP: multivariable regression task using the CUP dataset given by course professor Alessio Micheli.