Lasso, the

Abstract

Abstract The LASSO (least absolute shrinkage and selection operator) is a method of estimation in linear regression (and related) models that combines shrinkage estimation achieved in ridge regression with model selection where some (or all) parameter estimates are set to zero. The LASSO is capable of producing a “sparse” estimate of the parameter and can be used effectively even when the number of parameters exceeds the number of observations. LASSO estimates can be computed very efficiently using a number of methods, including coordinate descent methods. A number of generalizations of the LASSO have been proposed, including the fused LASSO, the group LASSO, and the adaptive LASSO.