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 |
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 |
Reference manual: | kernelshap.pdf |
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 imports: | SEMdeep, survex, XAItest |
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