kernelshap: Kernel SHAP

Efficient implementation of Kernel SHAP (Lundberg and Lee, 2017, <doi:10.48550/arXiv.1705.07874>) permutation SHAP, and additive SHAP for model interpretability. For Kernel SHAP and permutation SHAP, if the number of features is too large for exact calculations, the algorithms iterate until the SHAP values are sufficiently precise in terms of their standard errors. The package integrates smoothly with meta-learning packages such as 'tidymodels', 'caret' or 'mlr3'. It supports multi-output models, case weights, and parallel computations. Visualizations can be done using the R package 'shapviz'.

Version: 0.8.0
Depends: R (≥ 3.2.0)
Imports: foreach, MASS, stats, utils
Suggests: doFuture, testthat (≥ 3.0.0)
Published: 2025-07-08
DOI: 10.32614/CRAN.package.kernelshap
Author: Michael Mayer ORCID iD [aut, cre], David Watson ORCID iD [aut], Przemyslaw Biecek ORCID iD [ctb]
Maintainer: Michael Mayer <mayermichael79 at gmail.com>
BugReports: https://github.com/ModelOriented/kernelshap/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ModelOriented/kernelshap
NeedsCompilation: no
Materials: README NEWS
In views: MachineLearning
CRAN checks: kernelshap results

Documentation:

Reference manual: kernelshap.pdf

Downloads:

Package source: kernelshap_0.8.0.tar.gz
Windows binaries: r-devel: kernelshap_0.7.0.zip, r-release: kernelshap_0.7.0.zip, r-oldrel: kernelshap_0.7.0.zip
macOS binaries: r-release (arm64): kernelshap_0.7.0.tgz, r-oldrel (arm64): kernelshap_0.7.0.tgz, r-release (x86_64): kernelshap_0.7.0.tgz, r-oldrel (x86_64): kernelshap_0.7.0.tgz
Old sources: kernelshap archive

Reverse dependencies:

Reverse imports: SEMdeep, survex, XAItest

Linking:

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