Sparse linear models with demonstrations using GLMNET

Trevor Hastie, Ph.D.
Stanford University

ABSTRACT:
Focusing on R package glmnet, I will talk about efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. The algorithm uses cyclical coordinate descent in a pathwise fashion. I will also touch on two recent additions, multiple-response Gaussian and grouped multinomial.