DexGroves/gbm-lrd: Generalized Boosted Regression Models

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).

Getting started

Package details

AuthorGreg Ridgeway <[email protected]> with contributions from others
MaintainerHarry Southworth <[email protected]>
LicenseGPL (>= 2) | file LICENSE
Version2.1-06
URL https://github.com/harrysouthworth/gbm
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("DexGroves/gbm-lrd")
DexGroves/gbm-lrd documentation built on June 2, 2017, 4:30 a.m.