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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 papers listed in the URL below.

copied from cf-post-staging / r-glmnet
Type Size Name Uploaded Downloads Labels
conda 1.8 MB | linux-ppc64le/r-glmnet-4.1-r36ha9c7abe_0.tar.bz2  5 years and 2 months ago 73 main
conda 1.8 MB | win-64/r-glmnet-4.1-r36he816bda_0.tar.bz2  5 years and 2 months ago 1158 main
conda 1.8 MB | win-64/r-glmnet-4.1-r40he816bda_0.tar.bz2  5 years and 2 months ago 1560 main
conda 1.8 MB | linux-ppc64le/r-glmnet-4.1-r40ha9c7abe_0.tar.bz2  5 years and 2 months ago 76 main
conda 1.8 MB | linux-aarch64/r-glmnet-4.1-r36h6fc6016_0.tar.bz2  5 years and 2 months ago 129 main
conda 1.8 MB | osx-64/r-glmnet-4.1-r40h1a6e9bf_0.tar.bz2  5 years and 2 months ago 694 main
conda 1.8 MB | osx-64/r-glmnet-4.1-r36h1a6e9bf_0.tar.bz2  5 years and 2 months ago 492 main
conda 1.8 MB | linux-64/r-glmnet-4.1-r36h859d828_0.tar.bz2  5 years and 2 months ago 4202 main
conda 1.8 MB | linux-64/r-glmnet-4.1-r40h859d828_0.tar.bz2  5 years and 2 months ago 5992 main
conda 1.8 MB | linux-aarch64/r-glmnet-4.1-r40h6fc6016_0.tar.bz2  5 years and 2 months ago 116 main

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