Introduction

This project is part of the Machine Learning exam for the Master's degree in Computer Science at Bicocca University.

The primary objective of this project is to develop and compare two supervised learning models using a specific dataset.

Project Overview

In this project, we have developed two supervised learning models: a Decision Tree and a Neural Network.

These models have been trained and evaluated on a dataset to accomplish a classification task.

Dataset

The dataset chosen for this project is www.kaggle.com/datasets/kukuroo3/body-signal-of-smoking. It was selected due to its relevance to the domain and suitability for demonstrating the capabilities of the chosen machine learning algorithms. The dataset comprises 27 features for over 50000 values.

Models

We used two models, Decision Tree and Neural Network both with and without the PCA.

Contributors

• Claudio Ricci

• Fabio Villa

Conclusion

This project showcases the application of machine learning techniques, specifically Decision Trees and Neural Networks, in solving real-world problems. We hope this repository serves as a valuable resource for learning and experimentation in the field of machine learning.

If you have any questions, suggestions, or contributions, feel free to reach out to the project contributors. Thank you for your interest!