gbm: Generalized Boosted Regression Models
Version 2.1.3

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).

Package details

AuthorGreg Ridgeway <[email protected]> with contributions from others
Date of publication2017-03-21 06:48:03 UTC
LicenseGPL (>= 2) | file LICENSE
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the gbm package in your browser

Any scripts or data that you put into this service are public.

gbm documentation built on May 30, 2017, 4:38 a.m.