Ridge Regression in R (Step-by-Step)

Ridge regression is a method we can use to fit a regression model when multicollinearity is present in the data. This second term in the equation is known as a shrinkage penalty. In ridge regression, we select a value for λ that produces the lowest possible test MSE (mean squared error). This tutorial provides a step-by-step example of how to perform ridge regression in R. For this example, we'll use the R built-in dataset called mtcars. To perform ridge regression, we'll use functions from the glmnet package.