In this recipe, we'll learn about ridge regression. It is different from vanilla linear regression; it introduces a regularization parameter to shrink coefficients. This is useful when the dataset has collinear factors.
Using ridge regression to overcome linear regression's shortfalls
Getting ready
Let's load a dataset that has a low effective rank and compare ridge regression with linear regression by way of the coefficients. If you're not familiar with rank, it's the smaller of the linearly independent columns and the linearly...