R Observatory: Metrics for treeshap version 0.4.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

treeshap

0.4.0Package record

Compute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP' Algorithm

0packages dependsuggested by 3

7Kdownloads / year

71.6%test coverage

13/13flavors OK

Overview

About

Maintained by Michael MayerCRAN page ↗GitHub ↗Website ↗Issues ↗

An efficient implementation of the 'TreeSHAP' algorithm introduced by Lundberg et al., (2020) doi:10.1038/s42256-019-0138-9. It is capable of calculating SHAP (SHapley Additive exPlanations) values for tree-based models in polynomial time. Currently supported models include 'gbm', 'randomForest', 'ranger', 'xgboost', 'lightgbm'.

Changes in 0.4.0

Cleanup in #52 (https://github.com/ModelOriented/treeshap/pull/52). Thanks @kapsner
Fixed xgboost api and add depends R>=4.1.0 as in #51 (https://github.com/ModelOriented/treeshap/pull/51). Thanks @kapsner
Fix ranger.unify for probability forests as in #43 (https://github.com/ModelOriented/treeshap/pull/43). Thanks @ck37
Added support for GPBoost as in #41 (https://github.com/ModelOriented/treeshap/pull/41). Thanks @fabsig

From NEWS.md in the release

Install

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

install.packages("treeshap", 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("ModelOriented/treeshap")

Development version from ModelOriented/treeshap. 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-treeshap

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-treeshap

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-treeshap

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: 5.2 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK6 OK2026-04-25

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.4.0

README· In the repository, left out of the releaseVignettesNoNEWSYes · 100% structured · mentions 0.4.0Citation fileNoWebsiteYes · pkgdown

Help pages: 28
Examples that run: 27%4 run in a plain check (4 of them under a condition) · 11 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 78%
Documented parameters: 99%
Return-value docs: 100%
Help pages citing references: 0%

How these are measured

Downloads

7K

CRAN downloads in the past year

Rank #3,420 · ~19/day · ~582/mo

Releases R versions

Daily download trend is not available in this view yet.

1.1K30 days

3.2K90 days

7K1 year

Compare downloads with other packages →

Also on377 r2u4 autocran

How downloads are counted

Repository

modeloriented/treeshap ↗Organization: ModelOriented

106Stars

25Forks

7Open issues

1Open PRs

4Releases

262Commits

10Commit identities

explainabilityexplainable-aiexplainable-artificial-intelligenceexplanatory-model-analysisimlinterpretabilityinterpretable-machine-learningmachine-learning

License file reads as GPL-3.0 · 262 commits · Last activity 2026-04-24 · +1.9% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 632
Median days to close, 50 most recently updated closed PRs: 2

Stars over time

2025-10-22 · 892026-10-21 · 106

How these are measured

PracticesBeta

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

Checks run against github.com/modeloriented/treeshap on 2026-10-21.

Continuous integration (2)

GitHub ActionsR CMD check workflow

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

Docs source (4)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-05-02 · The repository has a site deploy workflow

Coverage (1)

Coverage reporting

Reproducibility and dev environment (1)

data-raw/

Show all practicesHide 2 practices

CRAN release process (2)

cran-comments.mdrevdep/

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v4 (2026-10-20)

AI coding toolsBeta

This repository shows signs of AI coding tools.

GitHub Copilotfirst seen 2026-05-13
Pull request: opened by its own account

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

Dependencies

Declared dependencies

13 external dependencies (excludes base and recommended)

Installing treeshap adds 19 packages (9 with compiled code, 21 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, Rcpp 1.8 MB.

Depends (1)

R >= 4.1.0

Imports (3)

data.table ggplot2 Rcpp

LinkingTo (1)

Rcpp

Suggests (10)

gbm jsonlite lightgbm gpboost randomForest ranger scalessurvivaltestthat xgboost

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Suggested by 3

Suggests, most downloaded first

survex AgriFusionR ubair

How these are counted

Code & Tests

Datasets

People & History

People (8)

Michael Mayer

Author, Maintainer since 0.4.0 (2026) · added in 0.4.0

Przemyslaw Biecek

Author, Copyright holder

Author

Author

Author

Contributor

Contributor

Contributor

Previously maintained by Mateusz Krzyzinski (0.2.5 to 0.3.1).

Releases (4)

Pick two releases to compare their code metrics.

unarchivedReturned to CRAN
2026-04-24
0.4.0Latest
record
2026-04-24 · current release · diff ↗ ·
added 1 export
gpboost.unify
R
R 4.6.0 released · 2026-04-24
archivedRemoved from CRAN
2025-12-17
issues were not corrected in time
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
unarchivedReturned to CRAN
2024-01-22
0.3.1
record
2024-01-22 · diff ↗
archivedRemoved from CRAN
2024-01-11
issues were not corrected in time
0.3.0
record
2023-10-24 · diff ↗
0.2.5
record
2023-10-01
R
R 4.3.0 released · 2023-04-21

Package metadata

First published: 2023-10-01
Total releases: 4 / 3 yrs
License: GPL-3 OSI
Minimum R: ≥ 4.1.0
Bundled data: 623 KB / 1 file
Download size: 808 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("treeshap")

Format

Mayer, M., Biecek, P., Kapsner, L. A., Komisarczyk, K., Kozminski, P., Krzyzinski, M., Maksymiuk, S., & Spytek, M. (2026). treeshap: Compute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP' Algorithm (Version 0.4.0) [Computer software]. https://doi.org/10.32614/CRAN.package.treeshap

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 treeshap version 0.4.0 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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