gbm v0.6
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Generalized Boosted Regression Models
This package implements extensions
to Freund and Schapire's AdaBoost algorithm and J. Friedman's
gradient boosting machine. Includes regression methods for least
squares, absolute loss, logistic, Poisson, Cox proportional hazards
partial likelihood, and AdaBoost exponential loss.
Functions in gbm
| Name | Description | |
| gbm.perf | GBM performance | |
| calibrate.plot | Calibration plot | |
| predict.gbm | Predict method for GBM Model Fits | |
| gbm.object | Generalized Boosted Regression Model Object | |
| gbm | Generalized Boosted Regression Modeling | |
| quantile.rug | Quantile rug plot | |
| plot.gbm | Marginal plots of fitted gbm objects | |
| pretty.gbm.tree | Print gbm tree components | |
| summary.gbm | Summary of a gbm object | |
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Details
| Date | 2003-02-18 |
| License | GPL (version 2 or newer) |
| URL | http://www.i-pensieri.com/gregr/gbm.shtml |
| depends | base (>= 1.6.0) , lattice , modreg , R (>= 1.6.0) , survival |
| Contributors | Greg Ridgeway |
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