glmnet v1.8-5
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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 | |
| predict.glmnet | make predictions from a "glmnet" object. | |
| glmnet | fit a GLM with lasso or elasticnet regularization | |
| deviance.glmnet | Extract the deviance from a glmnet object | |
| glmnet-package | Elastic net model paths for some generalized linear models | |
| print.glmnet | print a glmnet object | |
| cv.glmnet | Cross-validation for glmnet | |
| glmnet-internal | Internal glmnet functions | |
| predict.cv.glmnet | make predictions from a "cv.glmnet" object. | |
| plot.cv.glmnet | plot the cross-validation curve produced by cv.glmnet | |
| plot.glmnet | plot coefficients from a "glmnet" object | |
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Details
| Type | Package |
| Date | 2012-12-31 |
| License | GPL-2 |
| URL | http://www.jstatsoft.org/v33/i01/. |
| Packaged | 2012-12-31 19:26:08 UTC; hastie |
| Repository | CRAN |
| Date/Publication | 2013-01-04 09:21:44 |
| depends | Matrix (>= 1.0-6) , utils |
| suggests | survival |
| Contributors | Rob Tibshirani, Trevor Hastie, Jerome Friedman |
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