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Package: xgboost
Type: Package
Title: eXtreme Gradient Boosting
Version: 0.4-0
Title: Extreme Gradient Boosting
Version: 0.4-1
Date: 2015-05-11
Author: Tianqi Chen <tianqi.tchen@gmail.com>, Tong He <hetong007@gmail.com>, Michael Benesty <michael@benesty.fr>
Maintainer: Tong He <hetong007@gmail.com>
Description: eXtreme Gradient Boosting, which is an
efficient and scalable implementation of gradient boosting framework.
This package is an R wrapper of xgboost. The package includes efficient
Description: Extreme Gradient Boosting, which is an
efficient implementation of gradient boosting framework.
This package is its R interface. 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
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.