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shapper: Wrapper of Python Library 'shap'

Provides SHAP explanations of machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the Interpretable Machine Learning, there are more and more new ideas for explaining black-box models. One of the best known method for local explanations is SHapley Additive exPlanations (SHAP) introduced by Lundberg, S., et al., (2016) <doi:10.48550/arXiv.1705.07874> The SHAP method is used to calculate influences of variables on the particular observation. This method is based on Shapley values, a technique used in game theory. The R package 'shapper' is a port of the Python library 'shap'.

Version: 0.1.3
Imports: reticulate, DALEX, ggplot2
Suggests: covr, knitr, randomForest, rpart, testthat, markdown, qpdf
Published: 2020-08-28
DOI: 10.32614/CRAN.package.shapper
Author: Szymon Maksymiuk [aut, cre], Alicja Gosiewska [aut], Przemyslaw Biecek [aut], Mateusz Staniak [ctb], Michal Burdukiewicz [ctb]
Maintainer: Szymon Maksymiuk <sz.maksymiuk at gmail.com>
BugReports: https://github.com/ModelOriented/shapper/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/ModelOriented/shapper
NeedsCompilation: no
Materials: NEWS
In views: MachineLearning
CRAN checks: shapper results

Documentation:

Reference manual: shapper.pdf
Vignettes: How to use shapper for classification
How to use shapper for regression

Downloads:

Package source: shapper_0.1.3.tar.gz
Windows binaries: r-devel: shapper_0.1.3.zip, r-release: shapper_0.1.3.zip, r-oldrel: shapper_0.1.3.zip
macOS binaries: r-release (arm64): shapper_0.1.3.tgz, r-oldrel (arm64): shapper_0.1.3.tgz, r-release (x86_64): shapper_0.1.3.tgz, r-oldrel (x86_64): shapper_0.1.3.tgz
Old sources: shapper archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=shapper to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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