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 multiresponse gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a pathwise fashion, as described in the paper listed below.
| Version: | 1.9-3 |
| Depends: | Matrix (≥ 1.0-6), utils |
| Suggests: | survival |
| Published: | 2013-03-02 |
| Author: | Jerome Friedman, Trevor Hastie, 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 |
| In views: | MachineLearning |
| CRAN checks: | glmnet results |
| Package source: | glmnet_1.9-3.tar.gz |
| MacOS X binary: | glmnet_1.9-3.tgz |
| Windows binary: | glmnet_1.9-3.zip |
| Reference manual: | glmnet.pdf |
| Vignettes: |
Fitting the Penalized Cox Model |
| News/ChangeLog: | ChangeLog |
| Old sources: | glmnet archive |
| Reverse depends: | aBioMarVsuit, anoint, bigdata, BigTSP, BioMark, c060, cosso, covTest, DivMelt, fastVAR, FindIt, glmnetcr, hdlm, KsPlot, mht, msr, oblique.tree, pacose, parcor, PAS, polywog, refund, relaxnet, RTextTools, RVtests, sparsenet, TextRegression |
| Reverse imports: | c060, Causata, FindIt |
| Reverse suggests: | caret, catdata, fscaret, pmml, ppstat, randomForestSRC, SuperLearner |