Generalized Boosted Regression Models R package gbm version 2.3.1 CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning) CRAN Task View: Survival (https://CRAN.R-project.org/view=Survival) 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 <https://github.com/gbm-developers/gbm3>. Software Depends: R (>= 3.5.0) Imports: lattice, parallel, survival Suggests: bookdown, gridExtra, knitr, pdp, rmarkdown, RUnit, splines, testthat (>= 3.0.0), viridis, MASS Greg Ridgeway <gridge@upenn.edu> Comprehensive R Archive Network (CRAN) Greg Ridgeway [aut, cre] (ORCID: <https://orcid.org/0000-0001-6911-0804>), Daniel Edwards [ctb], Brian Kriegler [ctb], Stefan Schroedl [ctb], Harry Southworth [ctb], Brandon Greenwell [ctb] (ORCID: <https://orcid.org/0000-0002-8120-0084>), Bradley Boehmke [ctb] (ORCID: <https://orcid.org/0000-0002-3611-8516>), Jay Cunningham [ctb], GBM Developers [aut] (https://github.com/gbm-developers) GPL (>= 2) file LICENSE (https://CRAN.R-project.org/package=gbm/LICENSE) 2026-07-09 application/tgz https://CRAN.R-project.org/package=gbm doi:10.32614/CRAN.package.gbm