Package: xgboost
Type: Package
Title: Extreme Gradient Boosting
Version: 3.2.1.1
Date: 2026-03-18
Authors@R: c(
  person("Tianqi", "Chen", role = c("aut"),
         email = "tianqi.tchen@gmail.com"),
  person("Tong", "He", role = c("aut"),
         email = "hetong007@gmail.com"),
  person("Michael", "Benesty", role = c("aut"),
         email = "michael@benesty.fr"),
  person("Vadim", "Khotilovich", role = c("aut"),
         email = "khotilovich@gmail.com"),
  person("Yuan", "Tang", role = c("aut"),
         email = "terrytangyuan@gmail.com",
         comment = c(ORCID = "0000-0001-5243-233X")),
  person("Hyunsu", "Cho", role = c("aut"),
         email = "chohyu01@cs.washington.edu"),
  person("Kailong", "Chen", role = c("aut")),
  person("Rory", "Mitchell", role = c("aut")),
  person("Ignacio", "Cano", role = c("aut")),
  person("Tianyi", "Zhou", role = c("aut")),
  person("Mu", "Li", role = c("aut")),
  person("Junyuan", "Xie", role = c("aut")),
  person("Min", "Lin", role = c("aut")),
  person("Yifeng", "Geng", role = c("aut")),
  person("Yutian", "Li", role = c("aut")),
  person("Jiaming", "Yuan", role = c("aut", "cre"),
         email = "jm.yuan@outlook.com"),
  person("David", "Cortes", role = c("aut")),
  person("XGBoost contributors", role = c("cph"),
         comment = "base XGBoost implementation")
  )
Maintainer: Jiaming Yuan <jm.yuan@outlook.com>
Description: 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.
License: Apache License (== 2.0) | file LICENSE
URL: https://github.com/dmlc/xgboost
BugReports: https://github.com/dmlc/xgboost/issues
NeedsCompilation: yes
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, ggplot2 (>= 1.0.1), DiagrammeR (>= 0.9.0),
        DiagrammeRsvg, rsvg, htmlwidgets, Ckmeans.1d.dp (>= 3.3.1), vcd
        (>= 1.3), testthat, igraph (>= 1.0.1), float, titanic,
        RhpcBLASctl, survival
Depends: R (>= 4.3.0)
Imports: Matrix (>= 1.1-0), methods, data.table (>= 1.9.6), jsonlite
        (>= 1.0)
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Encoding: UTF-8
SystemRequirements: GNU make, C++17
Config/pak/sysreqs: make
Repository: https://dmlc.r-universe.dev
Date/Publication: 2026-03-17 18:30:16 UTC
RemoteUrl: https://github.com/dmlc/xgboost
RemoteRef: release_3.2.0
RemoteSha: acb7b7f48542c315ef571a4f2836c1d1149b3e4f
RemoteSubdir: R-package
Packaged: 2026-06-15 08:06:11 UTC; root
Author: Tianqi Chen [aut],
  Tong He [aut],
  Michael Benesty [aut],
  Vadim Khotilovich [aut],
  Yuan Tang [aut] (ORCID: <https://orcid.org/0000-0001-5243-233X>),
  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],
  Jiaming Yuan [aut, cre],
  David Cortes [aut],
  XGBoost contributors [cph] (base XGBoost implementation)