gbm: Generalized Boosted Regression Models
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: |
2.1.8.1 |
| Depends: |
R (≥ 2.9.0) |
| Imports: |
lattice, parallel, survival |
| Suggests: |
covr, gridExtra, knitr, pdp, RUnit, splines, tinytest, vip, viridis |
| Published: |
2022-08-11 |
| 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 |
Documentation:
Downloads:
Reverse dependencies:
| Reverse depends: |
gbm2sas, mma |
| Reverse imports: |
autoMrP, biomod2, Bodi, branchpointer, bst, bujar, crispRdesignR, DMLLZU, ebirdst, ecospat, EnsembleBase, EpiSemble, EZtune, gbm.auto, gbts, inTrees, lilikoi, LOGANTree, metaEnsembleR, MiDA, MLInterfaces, mob, mvGPS, paths, pomodoro, PSweight, regfilter, regressoR, RSDA, scorecardModelUtils, SDMtune, spm, spm2, SSDM, statVisual, stepgbm, traineR, tsensembler, twang, twangContinuous, twangMediation, visualpred |
| Reverse suggests: |
BiodiversityR, caretEnsemble, cheem, ciu, CMA, condvis2, corrgrapher, creditmodel, crimelinkage, cvwrapr, DALEXtra, dismo, fairmodels, featurefinder, fscaret, imputeR, insight, LDLcalc, MachineShop, MatchIt, mboost, mlr, opera, pdp, phyloregion, plotmo, pmml, posterior, riskRegression, rSAFE, SDMPlay, shapr, subsemble, SuperLearner, superMICE, survex, triplot, vip, WeightIt |
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