Predicting Car Price using Machine Learning

Description

Summary

• Problem Description: Correlation among independent variables: We’ll first start off with an arbitrary number of features, and then use the “statsmodels” library to build models using the shortlisted features (this is because sklearn doesn’t have adjusted r-squared but statsmodels has).
• The values of r-squared and adjusted r-squared are computed based on the training set, though we must always look at metrics computed on the test set.