Extremely 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. Two recent additions are the multiple-response Gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.
Version: | 2.0-3 |
Depends: | Matrix (≥ 1.0-6), utils, foreach |
Imports: | methods |
Suggests: | survival, knitr, lars |
Published: | 2016-02-23 |
Author: | Jerome Friedman, Trevor Hastie, Noah Simon, Rob Tibshirani |
Maintainer: | Trevor Hastie <hastie at stanford.edu> |
License: | GPL-2 |
URL: | http://www.jstatsoft.org/v33/i01/. |
NeedsCompilation: | yes |
Citation: | glmnet citation info |
Materials: | ChangeLog |
In views: | MachineLearning |
CRAN checks: | glmnet results |
Reference manual: | glmnet.pdf |
Vignettes: |
An Introduction to Glmnet Fitting the Penalized Cox Model |
Package source: | glmnet_2.0-3.tar.gz |
Windows binaries: | r-devel: glmnet_2.0-3.zip, r-release: glmnet_2.0-3.zip, r-oldrel: glmnet_2.0-3.zip |
OS X Snow Leopard binaries: | r-release: glmnet_2.0-3.tgz, r-oldrel: glmnet_2.0-2.tgz |
OS X Mavericks binaries: | r-release: glmnet_2.0-3.tgz |
Old sources: | glmnet archive |