[aut, cre],
Bradley Boehmke
[aut],
Jay Cunningham [aut],
GBM Developers [aut] (https://github.com/gbm-developers)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.
| Version: | 2.1.8 |
| Depends: | R (≥ 2.9.0) |
| Imports: | lattice, parallel, survival |
| Suggests: | covr, gridExtra, knitr, pdp, RUnit, splines, tinytest, vip, viridis |
| Published: | 2020-07-15 |
| Author: | Brandon Greenwell
[aut, cre],
Bradley Boehmke
[aut],
Jay Cunningham [aut],
GBM Developers [aut] (https://github.com/gbm-developers) |
| Maintainer: | Brandon Greenwell <greenwell.brandon at gmail.com> |
| 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_2.1.8.tar.gz |
| Windows binaries: | r-devel: gbm_2.1.8.zip, r-release: gbm_2.1.8.zip, r-oldrel: gbm_2.1.8.zip |
| macOS binaries: | r-release: gbm_2.1.8.tgz, r-oldrel: gbm_2.1.8.tgz |
| Old sources: | gbm archive |
| Reverse depends: | BigTSP, ecospat, gbm2sas, mma, personalized, SRGnet, twang |
| Reverse imports: | aurelius, biomod2, branchpointer, bst, bujar, crispRdesignR, EnsembleBase, EZtune, gbts, horserule, inTrees, IPMRF, MiDA, MLInterfaces, mob, OmicsMarkeR, paths, Plasmode, regressoR, scorecardModelUtils, SDMPlay, SDMtune, simulatorZ, spm, SSDM, statVisual |
| Reverse suggests: | BiodiversityR, caretEnsemble, casebase, CMA, corrgrapher, creditmodel, crimelinkage, DALEXtra, dismo, featurefinder, fscaret, imputeR, insight, MachineShop, mboost, mlr, opera, pdp, plotmo, pmml, riskRegression, SuperLearner, triplot, vip, WeightIt |
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