xgboost: Extreme Gradient Boosting
Version 0.6-4

Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) . This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.

Package details

AuthorTianqi Chen <tianqi.tchen@gmail.com>, Tong He <hetong007@gmail.com>, Michael Benesty <michael@benesty.fr>, Vadim Khotilovich <khotilovich@gmail.com>, Yuan Tang <terrytangyuan@gmail.com>
Date of publication2017-01-05 10:40:06
MaintainerTong He <hetong007@gmail.com>
LicenseApache License (== 2.0) | file LICENSE
Version0.6-4
URL https://github.com/dmlc/xgboost
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("xgboost")

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xgboost documentation built on May 29, 2017, 5:48 p.m.