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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. Newer version available at github.com/gbm-developers/gbm3.
Version: | 2.2.2 |
Depends: | R (≥ 2.9.0) |
Imports: | lattice, parallel, survival |
Suggests: | covr, gridExtra, knitr, pdp, RUnit, splines, tinytest, vip, viridis |
Published: | 2024-06-28 |
DOI: | 10.32614/CRAN.package.gbm |
Author: | Greg Ridgeway [aut, cre], Daniel Edwards [ctb], Brian Kriegler [ctb], Stefan Schroedl [ctb], Harry Southworth [ctb], Brandon Greenwell [ctb], Bradley Boehmke [ctb], Jay Cunningham [ctb], GBM Developers [aut] (https://github.com/gbm-developers) |
Maintainer: | Greg Ridgeway <gridge at upenn.edu> |
BugReports: | https://github.com/gbm-developers/gbm/issues |
License: | GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE] |
URL: | https://github.com/gbm-developers/gbm |
NeedsCompilation: | yes |
Materials: | README NEWS |
In views: | MachineLearning, Survival |
CRAN checks: | gbm results |
Reference manual: | gbm.pdf |
Vignettes: |
Generalized Boosted Models: A guide to the gbm package |
Package source: | gbm_2.2.2.tar.gz |
Windows binaries: | r-devel: gbm_2.2.2.zip, r-release: gbm_2.2.2.zip, r-oldrel: gbm_2.2.2.zip |
macOS binaries: | r-release (arm64): gbm_2.2.2.tgz, r-oldrel (arm64): gbm_2.2.2.tgz, r-release (x86_64): gbm_2.2.2.tgz, r-oldrel (x86_64): gbm_2.2.2.tgz |
Old sources: | gbm archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.