glmnet v1.9-5
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Lasso and elastic-net regularized generalized linear models
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.
Functions in glmnet
| Name | Description | |
| print.glmnet | print a glmnet object | |
| cv.glmnet | Cross-validation for glmnet | |
| predict.cv.glmnet | make predictions from a "cv.glmnet" object. | |
| glmnet-package | Elastic net model paths for some generalized linear models | |
| plot.cv.glmnet | plot the cross-validation curve produced by cv.glmnet | |
| glmnet | fit a GLM with lasso or elasticnet regularization | |
| plot.glmnet | plot coefficients from a "glmnet" object | |
| glmnet.control | internal glmnet parameters | |
| predict.glmnet | make predictions from a "glmnet" object. | |
| deviance.glmnet | Extract the deviance from a glmnet object | |
| glmnet-internal | Internal glmnet functions | |
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Details
| Type | Package |
| Date | 2013-8-1 |
| License | GPL-2 |
| URL | http://www.jstatsoft.org/v33/i01/. |
| Packaged | 2013-08-03 23:54:11 UTC; hastie |
| NeedsCompilation | yes |
| Repository | CRAN |
| Date/Publication | 2013-08-04 02:09:50 |
| suggests | foreach , survival |
| depends | Matrix (>= 1.0-6) , utils |
| Contributors | Rob Tibshirani, Trevor Hastie, Jerome Friedman |
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