xgboost

Extreme Gradient Boosting

Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. 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.

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Description file content

Package
xgboost
Type
Package
Title
Extreme Gradient Boosting
Version
0.71.2
Date
2018-06-08
Description
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.
License
Apache License (== 2.0) | file LICENSE
URL
BugReports
https://github.com/dmlc/xgboost/issues
NeedsCompilation
yes
VignetteBuilder
knitr
Suggests
knitr, rmarkdown, ggplot2 (>= 1.0.1), DiagrammeR (>= 0.9.0), Ckmeans.1d.dp (>= 3.3.1), vcd (>= 1.3), testthat, lintr, igraph (>= 1.0.1)
Depends
R (>= 3.3.0)
Imports
Matrix (>= 1.1-0), methods, data.table (>= 1.9.6), magrittr (>= 1.5), stringi (>= 0.5.2)
RoxygenNote
6.0.1
SystemRequirements
GNU make, C++11
Packaged
2018-06-08 21:49:47 UTC; ubuntu
Author
Tianqi Chen [aut], Tong He [aut, cre], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut] (), Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifeng Geng [aut], Yutian Li [aut], XGBoost contributors [cph] (base XGBoost implementation)
Maintainer
Tong He
Repository
CRAN
Date/Publication
2018-06-09 04:24:25 UTC

install.packages('xgboost')

0.71.2

2 months ago

https://github.com/dmlc/xgboost

Tong He

Apache License (== 2.0) | file LICENSE

Depends on

R (>= 3.3.0)

Imports

Matrix (>= 1.1-0), methods, data.table (>= 1.9.6), magrittr (>= 1.5), stringi (>= 0.5.2)

Suggests

knitr, rmarkdown, ggplot2 (>= 1.0.1), DiagrammeR (>= 0.9.0), Ckmeans.1d.dp (>= 3.3.1), vcd (>= 1.3), testthat, lintr, igraph (>= 1.0.1)

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