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An implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway.

Type Size Name Uploaded Downloads Labels
conda 598.1 kB | linux-64/r-gbm-2.1.8.1-r43h884c59f_0.tar.bz2  1 year and 2 months ago 55 main
conda 598.8 kB | linux-64/r-gbm-2.1.8-r42h884c59f_0.tar.bz2  2 years and 9 months ago 91 main
conda 615.4 kB | win-64/r-gbm-2.1.5-r36h796a38f_0.tar.bz2  5 years and 24 days ago 108 main
conda 603.1 kB | osx-64/r-gbm-2.1.5-r36h466af19_0.tar.bz2  5 years and 24 days ago 30 main
conda 605.8 kB | linux-64/r-gbm-2.1.5-r36h29659fb_0.tar.bz2  5 years and 24 days ago 6463 main

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