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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 1.7 MB | linux-ppc64le/r-glmnet-4.0-r40h2c7be84_0.tar.bz2  5 years and 10 months ago 75 main
conda 1.7 MB | linux-ppc64le/r-glmnet-4.0-r36h2c7be84_0.tar.bz2  5 years and 10 months ago 73 main
conda 1.7 MB | win-64/r-glmnet-4.0-r40h17ddedb_0.tar.bz2  5 years and 10 months ago 1263 main
conda 1.7 MB | win-64/r-glmnet-4.0-r36h17ddedb_0.tar.bz2  5 years and 10 months ago 1178 main
conda 1.7 MB | linux-aarch64/r-glmnet-4.0-r40h9bbef5b_0.tar.bz2  5 years and 10 months ago 115 main
conda 1.7 MB | osx-64/r-glmnet-4.0-r40h384270c_0.tar.bz2  5 years and 10 months ago 456 main
conda 1.7 MB | osx-64/r-glmnet-4.0-r36h384270c_0.tar.bz2  5 years and 10 months ago 478 main
conda 1.7 MB | linux-64/r-glmnet-4.0-r40h9bbef5b_0.tar.bz2  5 years and 10 months ago 4509 main
conda 1.7 MB | linux-64/r-glmnet-4.0-r36h9bbef5b_0.tar.bz2  5 years and 10 months ago 5345 main
conda 1.7 MB | linux-aarch64/r-glmnet-4.0-r36h9bbef5b_0.tar.bz2  5 years and 10 months ago 102 main

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