How it works...

Ridge regression is a regularization method where a penalty is imposed on the size of the coefficients. Ridge regression is identical to least squares, barring the fact that ridge coefficients are computed by decreasing a quantity that is somewhat different. In ridge regression, a scale transformation has a substantial effect. Therefore, to avoid obtaining different results depending on the predicted scale of measurement, it is advisable to standardize all predictors before estimating the model. To standardize the variables, we must subtract their means and divide by their standard deviations.