Implementing elastic net regression

Elastic net regression is a type of regression that combines lasso regression with ridge regression by adding L1 and L2 regularization terms to the loss function.

Getting ready

Implementing elastic net regression should be straightforward after the previous two recipes, so we will implement this in multiple linear regression on the iris dataset, instead of sticking to the two-dimensional data as before. We will use petal length, petal width, and sepal width to predict sepal length.

How to do it...

We proceed with the recipe as follows...