Computer Intelligence subject final project at UPC.

This R-based data science project on the UCI Parkinson's dataset employs machine learning (Decision tree, Random Forest, SVM, XGBoost) with a focus on hyperparameter tuning and feature selection. This repository showcases insights into Parkinson's disease prediction using effective data science practices.

The objective of this study is to accurately predict the motor and total UPDRS scores from the 16 voice measures using various Regression models