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Ridge Regression

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Repository containing the Statistical Methods for Machine Learning's project, academic year 2019/2020 Università degli Studi di Milano Instructor: Nicolò Cesa-Bianchi