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Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

copied from cf-post-staging / r-mboost
Type Size Name Uploaded Downloads Labels
conda 2.5 MB | win-64/r-mboost-2.9_6-r40h6d2157b_0.tar.bz2  4 years and 1 month ago 759 main
conda 2.4 MB | win-64/r-mboost-2.9_6-r41h6d2157b_0.tar.bz2  4 years and 1 month ago 748 main
conda 2.4 MB | osx-64/r-mboost-2.9_6-r40h0f1d5c4_0.tar.bz2  4 years and 1 month ago 114 main
conda 2.4 MB | osx-64/r-mboost-2.9_6-r41h0f1d5c4_0.tar.bz2  4 years and 1 month ago 113 main
conda 2.4 MB | linux-64/r-mboost-2.9_6-r40h06615bd_0.tar.bz2  4 years and 1 month ago 3127 main
conda 2.4 MB | linux-64/r-mboost-2.9_6-r41h06615bd_0.tar.bz2  4 years and 1 month ago 3058 main

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