Recently, I started working on Ridge and Lasso regularization for Linear and Logistic Regression. My doubts are given below:
- Is the penalty the same (by same proportion) for all the coefficients or is it based on variable importance? If it is the latter I believe we can directly apply regularization rather than spending time in feature selection.
- Whether the Multi-collinearity is taken care by ridge and lasso regularization?