Elastic Net (Model Selection)

Abstract An elastic net (EN) is an algorithm for fitting penalized regression models using a convex combination of the LASSO and ridge penalty norms. The algorithm takes advantage of both the sparsity property of the LASSO and variable grouping property of the ridge, making it a natural choice for model selection. EN estimates can be computed using LASSO‐based estimation methods, such as Least Angle Regression (LARS) or coordinate descent, and computational implementations of these methods are available in open‐source software packages.