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gbm (version 1.5-7)

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

25,231

Version

1.5-7

License

GPL (version 2 or newer)

Maintainer

Greg Ridgeway

Last Published

June 28th, 2024

Functions in gbm (1.5-7)

gbm.object

Generalized Boosted Regression Model Object
relative.influence

Methods for estimating relative influence
basehaz.gbm

Baseline hazard function
plot.gbm

Marginal plots of fitted gbm objects
gbm-package

Generalized Boosted Regression Models
gbm.perf

GBM performance
predict.gbm

Predict method for GBM Model Fits
gbm

Generalized Boosted Regression Modeling
shrink.gbm

L1 shrinkage of the predictor variables in a GBM
pretty.gbm.tree

Print gbm tree components
shrink.gbm.pred

Predictions from a shrunked GBM
summary.gbm

Summary of a gbm object
calibrate.plot

Calibration plot
quantile.rug

Quantile rug plot