This package is a R wrapper of xgboost, which is short for eXtreme Gradient Boosting. It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm. 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.
Version: | 0.3-2 |
Depends: | R (≥ 2.10) |
Imports: | Matrix (≥ 1.1-0), methods |
Published: | 2014-09-07 |
Author: | Tianqi Chen, Tong He |
Maintainer: | Tong He <hetong007 at gmail.com> |
BugReports: | https://github.com/tqchen/xgboost/issues |
License: | Apache License (== 2.0) | file LICENSE |
URL: | https://github.com/tqchen/xgboost |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | xgboost results |
Reference manual: | xgboost.pdf |
Package source: | xgboost_0.3-2.tar.gz |
Windows binaries: | r-devel: xgboost_0.3-2.zip, r-release: xgboost_0.3-2.zip, r-oldrel: xgboost_0.3-2.zip |
OS X Snow Leopard binaries: | r-release: xgboost_0.3-2.tgz, r-oldrel: xgboost_0.3-2.tgz |
OS X Mavericks binaries: | r-release: xgboost_0.3-2.tgz |
Old sources: | xgboost archive |
Reverse suggests: | mlr |