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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 2.7 MB | win-64/r-mboost-2.9_2.1-r36hda5aaf8_0.tar.bz2  5 years and 1 month ago 1038 main
conda 2.7 MB | win-64/r-mboost-2.9_2.1-r40hda5aaf8_0.tar.bz2  5 years and 1 month ago 1029 main
conda 2.6 MB | osx-64/r-mboost-2.9_2.1-r36h800e0f2_0.tar.bz2  5 years and 1 month ago 334 main
conda 2.7 MB | osx-64/r-mboost-2.9_2.1-r40h800e0f2_0.tar.bz2  5 years and 1 month ago 334 main
conda 2.6 MB | linux-64/r-mboost-2.9_2.1-r36hcdcec82_0.tar.bz2  5 years and 1 month ago 3456 main
conda 2.7 MB | linux-64/r-mboost-2.9_2.1-r40hcdcec82_0.tar.bz2  5 years and 1 month ago 3459 main

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