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gbm (version 1.2)

Generalized Boosted Regression Models

Description

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.

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Version

Install

install.packages('gbm')

Monthly Downloads

22,871

Version

1.2

License

GPL (version 2 or newer)

Maintainer

Greg Ridgeway

Last Published

June 28th, 2024

Functions in gbm (1.2)

calibrate.plot

Calibration plot
summary.gbm

Summary of a gbm object
relative.influence

Methods for estimating relative influence
gbm.perf

GBM performance
pretty.gbm.tree

Print gbm tree components
plot.gbm

Marginal plots of fitted gbm objects
quantile.rug

Quantile rug plot
gbm

Generalized Boosted Regression Modeling
predict.gbm

Predict method for GBM Model Fits
gbm.object

Generalized Boosted Regression Model Object