glmnet v2.0-9
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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 multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.
Functions in glmnet
| Name | Description | |
| deviance.glmnet | Extract the deviance from a glmnet object | |
| glmnet-internal | Internal glmnet functions | |
| beta_CVX | Simulated data for the glmnet vignette | |
| cv.glmnet | Cross-validation for glmnet | |
| plot.glmnet | plot coefficients from a "glmnet" object | |
| predict.cv.glmnet | make predictions from a "cv.glmnet" object. | |
| glmnet-package | ||
| glmnet | fit a GLM with lasso or elasticnet regularization | |
| glmnet.control | internal glmnet parameters | |
| plot.cv.glmnet | plot the cross-validation curve produced by cv.glmnet | |
| predict.glmnet | make predictions from a "glmnet" object. | |
| print.glmnet | print a glmnet object | |
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Details
| Type | Package |
| Date | 2017-05-01 |
| License | GPL-2 |
| VignetteBuilder | knitr |
| URL | http://www.jstatsoft.org/v33/i01/. |
| NeedsCompilation | yes |
| Packaged | 2017-05-02 17:33:24 UTC; hastie |
| Repository | CRAN |
| Date/Publication | 2017-05-02 20:39:42 UTC |
| depends | foreach , Matrix (>= 1.0-6) , utils |
| suggests | knitr , lars , survival |
| imports | methods |
| Contributors | Rob Tibshirani, Trevor Hastie, Jerome Friedman, Noah Simon |
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