/Home-Price-Prediction

Home price prediction with Lasso and Ridge Regression with parameter tuning

Primary LanguageJupyter NotebookMIT LicenseMIT

Home Price Prediction

Description

  1. Performed Lasso and Ridge Regression using Boston housing prices dataset and compared the performance by tuning the parameters and not tuning the parameters using cross validation.
  2. Tune the parameter alpha (regularization strength) for Ridge and Lasso using the validation set.
  3. Report the Mean Squared Error on the test set using the tuned parameters.
  4. Compare this result with the results you get without tuning the parameters.

Tools Requirement: Anaconda, Python

Current Version : v1.0.0.0

Last Update : 11.02.2016