This GitHub repository aims at predicting house prices given training and test house data of 20-dimensional features and comparing the performance of Ridge regression, LASSO and Elastic Net regression methods.
Input :
17385 20-dimensional housing data for training 4230 20-dimensional housing data for testing
Output:
Compute the regression weights and interpret them based on the methods allotted Plot the coefficient profiles of top 5 interesting features Evaluation of the models with Residual Sum of Squares (RSS) metric Some extra experiments (Bonus)