This package implements extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, quantile regression, logistic, Poisson, Cox proportional hazards partial likelihood, and AdaBoost exponential loss.
| Version: | 1.6-3.2 |
| Depends: | R (≥ 2.12.0), survival, lattice, splines |
| Suggests: | rpart |
| Published: | 2012-04-17 |
| Author: | Greg Ridgeway |
| Maintainer: | Greg Ridgeway <gregr at rand.org> |
| License: | GPL (≥ 2) |
| URL: | http://www.i-pensieri.com/gregr/gbm.shtml |
| In views: | MachineLearning, Survival |
| CRAN checks: | gbm results |
| Package source: | gbm_1.6-3.2.tar.gz |
| MacOS X binary: | gbm_1.6-3.2.tgz |
| Windows binary: | gbm_1.6-3.2.zip |
| Reference manual: | gbm.pdf |
| Vignettes: |
Generalized Boosted Models: A guide to the gbm package |
| Old sources: | gbm archive |
| Reverse depends: | bst, bujar, CompModSA, ModelMap, mseq, twang |
| Reverse suggests: | caret, dismo, mboost, soil.spec, SuperLearner |