Penalized Regression in R

Last Updated on August 15, 2020

In this post you will discover 3 recipes for penalized regression for the R platform.

You can copy and paste the recipes in this post to make a jump-start on your own problem or to learn and practice with linear regression in R.

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Each example in this post uses the longley dataset provided in the datasets package that comes with R. The longley dataset describes 7 economic variables observed from 1947 to 1962 used to predict the number of people employed yearly.

Ridge Regression

Ridge Regression creates a linear regression model that is penalized with the L2-norm which is the sum of the squared coefficients. This has the effect of shrinking the coefficient values (and the complexity of the model) allowing some coefficients with minor contribution to the
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