glmnet v2.0-4
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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. 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 | |
cv.glmnet | Cross-validation for glmnet | |
glmnet | fit a GLM with lasso or elasticnet regularization | |
glmnet-internal | Internal glmnet functions | |
beta_CVX | Simulated data for the glmnet vignette | |
predict.glmnet | make predictions from a "glmnet" object. | |
plot.cv.glmnet | plot the cross-validation curve produced by cv.glmnet | |
plot.glmnet | plot coefficients from a "glmnet" object | |
deviance.glmnet | Extract the deviance from a glmnet object | |
glmnet-package | Elastic net model paths for some generalized linear models | |
predict.cv.glmnet | make predictions from a "cv.glmnet" object. | |
glmnet.control | internal glmnet parameters | |
print.glmnet | print a glmnet object | |
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Details
Type | Package |
Date | 2016-3-12 |
License | GPL-2 |
VignetteBuilder | knitr |
URL | http://www.jstatsoft.org/v33/i01/. |
NeedsCompilation | yes |
Packaged | 2016-03-12 17:32:20 UTC; hastie |
Repository | CRAN |
Date/Publication | 2016-03-13 11:29:45 |
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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