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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.

copied from cf-staging / r-gbm

Installers

Info: This package contains files in non-standard labels.
  • linux-64 v2.2.2
  • linux-aarch64 v2.2.2
  • osx-64 v2.2.2
  • linux-ppc64le v2.2.2
  • win-64 v2.2.2

conda install

To install this package run one of the following:
conda install conda-forge::r-gbm
conda install conda-forge/label/cf201901::r-gbm
conda install conda-forge/label/cf202003::r-gbm
conda install conda-forge/label/gcc7::r-gbm

Description


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