R Observatory: Metrics for xgboost version 3.2.1.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

xgboost

3.2.1.1

Extreme Gradient Boosting

198packages depend

908.9Kdownloads / year

62.4%test coverage

13/13checks pass

Overview

About

Maintained by Jiaming YuanFirst published 2014-09-0142 releasesCRAN page ↗GitHub ↗

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.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("xgboost", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("dmlc/xgboost")

Development version from dmlc/xgboost. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-xgboost

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-xgboost

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-xgboost

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 29.9 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 0.59

62.4%

Coverage · measured lines

100%

Documentation · exports

4

Dependencies · direct

Check history

OK2026-08-04
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-06-08
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
WARNING2026-06-07
12 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
OK2026-04-25
12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Show 2 earlier snapshots

NOTE2026-03-19
11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
WARNING2026-03-10
10 OK · 3 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 93%
Return-value docs: 87%
References docs: 10%

Downloads

908.9K

CRAN downloads in the past year

Rank #424 · ~2.5K/day · ~75.7K/mo

Releases R versions

Daily download trend is not available in this view yet.

59.5K30 days

206.2K90 days

908.9K1 year

Compare downloads with other packages →

Also on44.4K r2u21 autocran135.7K conda_forge1.2K c2d4u

Repository

GitHub ↗ dmlc/xgboost

28,663Stars

8,883Forks

395Open issues

23Open PRs

78Releases

7,962Commits

699Contributors

gbdtgbrtgbmdistributed-systemsxgboostmachine-learning

License Apache-2.0 · 7,962 commits · Last activity 2026-08-18 · +0.3% stars, 30d

Stars over time

2025-08-16 · 27,0182026-08-18 · 28,663

Repository practices

Upstream repositoryBeta

9 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/dmlc/xgboost on 2026-08-16.

Continuous integration (1)

GitHub Actions

Automation and maintenance (2)

Dependabotpre-commit

Lint, format, editor (1)

EditorConfig

Governance and community (3)

Issue templatesFundingSecurity policy

Show all practices

Git structural (2)

.gitattributesSubmodules

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

16 external dependencies (excludes base and recommended)

Depends (1)

R >= 4.3.0

Imports (4)

Matrixmethodsdata.table jsonlite

LinkingTo (0)

none

Suggests (15)

knitr rmarkdown ggplot2 DiagrammeR DiagrammeRsvg rsvg htmlwidgets Ckmeans.1d.dp vcd testthat igraph float titanic RhpcBLASctlsurvival

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

198direct

42indirect

and 150 more packages.

Code & Tests

People & History

People (18)

Maintainer (1)

Jiaming Yuan

Author, Maintainer · added in 1.5.2.1

Authors (17)

Jiaming Yuan

Author, Maintainer · added in 1.5.2.1

Michael Benesty

Author · added in 0.3-3

Ignacio Cano

Author · added in 0.71.1

Kailong Chen

Author · added in 0.71.1

Tianqi Chen

Author

Hyunsu Cho

Author · added in 0.71.1

David Cortes

Author · added in 3.1.2.1

Yifeng Geng

Author · added in 0.71.1

Tong He

Author

Vadim Khotilovich

Author · added in 0.6-0

Mu Li

Author · added in 0.71.1

Yutian Li

Author · added in 0.71.1

Min Lin

Author · added in 0.71.1

Rory Mitchell

Author · added in 0.71.1

Yuan Tang

Author · added in 0.6-0

Junyuan Xie

Author · added in 0.71.1

Tianyi Zhou

Author · added in 0.71.1

Copyright holders (1)

XGBoost contributors

Copyright holder · added in 0.71.1

Package Timeline

42 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
3.2.1.1Latest
2026-03-18 · current release · diff ↗
3.2.0.1
2026-02-10 · diff ↗
3.1.3.1
2026-01-12 · diff ↗
3.1.2.1
2025-12-03 · diff ↗
1.7.11.1
2025-05-15 · diff ↗
1.7.10.1
2025-04-22 · diff ↗
R
R 4.5.0 released · 2025-04-11
1.7.9.1
2025-03-26 · diff ↗
1.7.8.1
2024-07-24 · diff ↗
R
R 4.4.0 released · 2024-04-24
1.7.7.1
2024-01-25 · diff ↗
1.7.6.1
2023-12-06 · diff ↗
R
R 4.3.0 released · 2023-04-21
1.7.5.1
2023-03-30 · diff ↗
1.7.3.1
2023-01-14 · diff ↗

Show 40 earlier events

R
R 4.2.0 released · 2022-04-22
1.6.0.1
2022-04-16 · diff ↗
1.5.2.1
2022-02-21 · diff ↗
1.5.0.2
2021-11-21 · diff ↗
1.5.0.1
2021-11-08 · diff ↗
R
R 4.1.0 released · 2021-05-18
1.4.1.1
2021-04-22 · diff ↗
1.3.2.1
2021-01-18 · diff ↗
1.3.1.1
2021-01-05 · diff ↗
1.2.0.1
2020-09-02 · diff ↗
1.1.1.1
2020-06-14 · diff ↗
R
R 4.0.0 released · 2020-04-24
1.0.0.2
2020-03-25 · diff ↗
1.0.0.1
2020-03-23 · diff ↗
0.90.0.2
2019-08-01 · diff ↗
0.90.0.1
2019-07-25 · diff ↗
R
R 3.6.0 released · 2019-04-26
0.82.1
2019-03-12 · diff ↗
0.81.0.1
2019-01-31 · diff ↗
0.71.2
2018-06-09 · diff ↗
0.71.1
2018-05-16 · diff ↗
R
R 3.5.0 released · 2018-04-23
0.6.4.1
2018-01-23 · diff ↗
R
R 3.4.0 released · 2017-04-21
0.6-4
2017-01-05 · diff ↗
0.6-3
2016-12-31 · diff ↗
0.6-2
2016-12-18 · diff ↗
0.6-0
2016-12-16 · diff ↗
0.4-4
2016-07-12 · diff ↗
R
R 3.3.0 released · 2016-05-03
0.4-3
2016-02-15 · diff ↗
0.4-2
2015-08-02 · diff ↗
0.4-1
2015-08-01 · diff ↗
R
R 3.2.0 released · 2015-04-16
archivedRemoved from CRAN
2015-03-13
code was not cross-platform, there were memory-access errors and check failures on Windows
0.3-3
2015-03-03 · diff ↗
0.3-2
2014-09-07 · diff ↗
0.3-1
2014-09-07 · diff ↗
0.3-0
2014-09-01
R
R 3.1.0 released · 2014-04-10

Package metadata

First published: 2014-09-01
Total releases: 42 / 12 yrs
License: Apache License (== 2.0) | file LICENSE
Minimum R: ≥ 4.3.0
Bundled data: 71 KB / 2 files
Download size: 1.5 MB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Databases with R High-Performance and Parallel Computing with R Machine Learning & Statistical Learning Model Deployment with R Survival Analysis

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("xgboost")

Format

Yuan, J., XGBoost contributors, Benesty, M., Cano, I., Chen, K., Chen, T., Cho, H., Cortes, D., Geng, Y., He, T., Khotilovich, V., Li, M., Li, Y., Lin, M., Mitchell, R., Tang, Y., Xie, J., & Zhou, T. (2026). xgboost: Extreme Gradient Boosting (Version 3.2.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.xgboost

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for xgboost version 3.2.1.1 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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