R Observatory: Metrics for lightgbm version 4.7.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

lightgbm

4.7.0Package record

Light Gradient Boosting Machine

15packages dependsuggested by 24

88.2Kdownloads / year

54.7%test coverage

13/13flavors OK

Overview

About

Maintained by James LambCRAN page ↗GitHub ↗Issues ↗

Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) https://proceedings.neurips.cc/paper/2017/hash/6449f44a102fde848669bdd9eb6b76fa-Abstract.html. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines.

Install

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

install.packages("lightgbm", 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("lightgbm-org/LightGBM")

Development version from lightgbm-org/LightGBM. 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-lightgbm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

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-lightgbm

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-lightgbm

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 16.0 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-07-27
WARNING9 OK, 3 NOTE, 2 WARNING2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 4.7.0

READMEYes · 2,099 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileNo

Help pages: 40 (3 internal)
Examples that run: 0%26 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 79%
Documented parameters: 100%
Return-value docs: 93%
Help pages citing references: 8%

Also includes 10 demo scripts (run with demo())

Vignettes (1)

Basic Walkthrough

How these are measured

Downloads

88.2K

CRAN downloads in the past year

Rank #1,384 · ~242/day · ~7.3K/mo

Releases R versions

Daily download trend is not available in this view yet.

6K30 days

19.8K90 days

88.2K1 year

Compare downloads with other packages →

Also on4K r2u3 autocran12.3K conda_forge124 c2d4u

How downloads are counted

Repository

lightgbm-org/lightgbm ↗Organization: lightgbm-org

18,903Stars

4,096Forks

447Open issues

89Open PRs

35Releases

3,896Commits

360Commit identities

gbdtgbmmachine-learningdata-miningdistributedlightgbmgbrtdecision-trees

License file reads as MIT · 3,896 commits · Last activity 2026-10-21 · +0.6% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 89%
Median days to close, 50 most recently updated closed issues: 14
Median days to close, 50 most recently updated closed PRs: 2

Stars over time

2026-07-19 · 18,5782026-10-22 · 18,903

How these are measured

PracticesBeta

14 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/lightgbm-org/lightgbm on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows

Governance and community (5)

Code of conductContributing guideIssue templatesSecurity policyCODEOWNERS

Docs source (1)

GitHub Pages site last deployed 2018-09-08

Automation and maintenance (2)

Dependabotpre-commit

Show all practicesHide 2 practices

Lint, format, editor (1)

EditorConfig

Git structural (3)

.gitattributesSubmodulesblame-ignore revs

How this is detected·Detection ruleset v3 (2026-09-26)

AI coding toolsBeta

This repository shows signs of AI coding tools.

GitHub Copilotfirst seen 2025-11-19
Pull request: opened by its own account

From outside contributors

Claude Code
Pull requests: 5 from outside contributors, first on 2026-03-31, 5 from forks
Cursor
Pull requests: 1 from outside contributors, first on 2026-10-05, 1 from forks

How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

7 external dependencies (excludes base and recommended)

Installing lightgbm adds 3 packages (2 with compiled code, 6.8 MB of source tarballs). Heaviest: data.table 5.7 MB, jsonlite 1.0 MB, R6 63 KB.

Depends (1)

R >= 4.0

Imports (8)

R6 data.tablegraphicsjsonlite (>= 1.0)Matrixmethodsparallelutils

LinkingTo (0)

none

Suggests (4)

knitr markdown RhpcBLASctl testthat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

15direct

0indirect

Imports 15

Suggested by 24

Show all 39 packagesHide all 39 packages

Depends, Imports or LinkingTo, most downloaded first

predhy funcml cbl MFF MIML sae.projection CGMissingDataR predhy.GUI evoFE imputeCGM FoRecoML mlS3 misspi ubair qshap

Suggests, most downloaded first

SHAPforxgboost tidypredict bonsai treeshap interflex PatientLevelPrediction sits orbital rtemis fastml spCF e2tree EIX comets BORG scorecraft qeML stackgbm ml r2pmml mlr3automl icarm mllrnrs lorax

How these are counted

Code & Tests

Datasets

People & History

People (21)

James Lamb

Author, Maintainer since 4.2.0 (2023)

Wei Chen

Author

David Cortes

Author · added in 3.3.0

Author

Author

Author

Author

Author

Author · added in 3.3.0

Damien Soukhavong

Author

Nikita Titov

Author · added in 3.3.0

Taifeng Wang

Author

Qiwei Ye

Author

IBM Corporation

Contributor · added in 3.0.0.2

Alberto Ferreira

Contributor · added in 3.2.0

Daniel Lemire

Contributor · added in 3.2.0

Michael Mayer

Contributor · added in 4.2.0

Yachen Yan

Contributor

Dropbox, Inc.

Copyright holder

Microsoft Corporation

Copyright holder

Victor Zverovich

Copyright holder · added in 3.2.0

Previously maintained by Yu Shi (3.3.0 to 3.3.5) and Guolin Ke (3.0.0 to 3.2.1).

Listed in earlier versions (3)

Show 3 peopleHide 3 people

Dave Daeschler

no longer listed · 3.0.0.2 to 3.3.5

Jay Loden

no longer listed · 3.0.0.2 to 3.3.5

Giampaolo Rodola

no longer listed · 3.0.0.2 to 3.3.5

Releases (18)

Pick two releases to compare their code metrics.

4.7.0Latest
record
2026-07-18 · current release · diff ↗ ·
added 1 export
lgb.interpret
R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
4.6.0
record
2025-02-13 · diff ↗
4.5.0
record
2024-07-26 · diff ↗
4.4.0
record
2024-06-15 · diff ↗ ·
removed 1 export
slice

added 1 export
lgb.slice.Dataset
R
R 4.4.0 released · 2024-04-24
4.3.0
record
2024-01-18 · diff ↗ ·
removed 2 exports
readRDS.lgb.Booster, saveRDS.lgb.Booster
4.2.0
record
2023-12-08 · diff ↗ ·
removed 3 exports
getinfo, lgb.unloader, setinfo

added 6 exports
getLGBMthreads, lgb.configure_fast_predict, lgb.drop_serialized, lgb.make_serializable, lgb.restore_handle, setLGBMthreads
R
R 4.3.0 released · 2023-04-21
3.3.5
record
2023-01-16 · diff ↗
3.3.4
record
2022-12-16 · diff ↗
3.3.3
record
2022-10-10 · diff ↗
R
R 4.2.0 released · 2022-04-22
3.3.2
record
2022-01-14 · diff ↗
unarchivedReturned to CRAN
2021-10-30

Show 13 earlier eventsHide 13 earlier events

3.3.1
record
2021-10-30 · diff ↗
archivedRemoved from CRAN
2021-10-25
check problems were not corrected in time
3.3.0
record
2021-10-09 · diff ↗ ·
added 2 exports
get_field, set_field
R
R 4.1.0 released · 2021-05-18
3.2.1
record
2021-04-13 · diff ↗
3.2.0
record
2021-03-22 · diff ↗
3.1.1
record
2020-12-08 · diff ↗
unarchivedReturned to CRAN
2020-11-19
3.1.0
record
2020-11-19 · diff ↗ ·
removed 4 exports
lgb.prepare, lgb.prepare2, lgb.prepare_rules, lgb.prepare_rules2
archivedRemoved from CRAN
2020-10-02
corrupting R's memory See the valgrind report of out-of-bounds write
3.0.0.2
record
2020-10-01 · diff ↗
3.0.0
record
2020-09-21
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2020-09-21
Total releases: 18 / 6 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.0
Bundled data: 128 KB / 3 files
Download size: 1.7 MB

Appears in task views

Machine Learning & Statistical Learning Model Deployment with R

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("lightgbm")

Format

Lamb, J., Dropbox, Inc., IBM Corporation, Microsoft Corporation, Chen, W., Cortes, D., Ferreira, A., Finley, T., Ke, G., Lemire, D., Liu, T., Ma, W., Mayer, M., Meng, Q., Shi, Y., Soukhavong, D., Titov, N., Wang, T., Yan, Y., Ye, Q., & Zverovich, V. (2026). lightgbm: Light Gradient Boosting Machine (Version 4.7.0) [Computer software]. https://doi.org/10.32614/CRAN.package.lightgbm

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 lightgbm version 4.7.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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