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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 615.4 kB | win-64/r-gbm-2.1.5-r36h796a38f_0.tar.bz2  5 years and 1 month ago 3 main
conda 603.1 kB | osx-64/r-gbm-2.1.5-r36h466af19_0.tar.bz2  5 years and 1 month ago 0 main
conda 605.8 kB | linux-64/r-gbm-2.1.5-r36h29659fb_0.tar.bz2  5 years and 1 month ago 1 main

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