shapviz: SHAP Visualizations

Visualizations for SHAP (SHapley Additive exPlanations), such as waterfall plots, force plots, various types of importance plots, dependence plots, and interaction plots. These plots act on a 'shapviz' object created from a matrix of SHAP values and a corresponding feature dataset. Wrappers for the R packages 'xgboost', 'lightgbm', 'fastshap', 'shapr', 'h2o', 'treeshap', 'DALEX', and 'kernelshap' are added for convenience. By separating visualization and computation, it is possible to display factor variables in graphs, even if the SHAP values are calculated by a model that requires numerical features. The plots are inspired by those provided by the 'shap' package in Python, but there is no dependency on it.

Version: 0.9.6
Depends: R (≥ 3.6.0)
Imports: ggfittext (≥ 0.8.0), gggenes, ggplot2 (≥ 3.4.0), ggrepel, grid, patchwork, rlang (≥ 0.3.0), stats, utils, xgboost
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Enhances: fastshap, h2o, lightgbm
Published: 2024-10-11
DOI: 10.32614/CRAN.package.shapviz
Author: Michael Mayer [aut, cre], Adrian Stando [ctb]
Maintainer: Michael Mayer <mayermichael79 at gmail.com>
BugReports: https://github.com/ModelOriented/shapviz/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ModelOriented/shapviz, https://modeloriented.github.io/shapviz/
NeedsCompilation: no
Materials: README NEWS
In views: MachineLearning
CRAN checks: shapviz results

Documentation:

Reference manual: shapviz.pdf
Vignettes: Using 'shapviz' (source, R code)
Geographic Components (source, R code)
Multiple 'shapviz' objects (source, R code)
Tidymodels and SHAP (source)

Downloads:

Package source: shapviz_0.9.6.tar.gz
Windows binaries: r-devel: shapviz_0.9.6.zip, r-release: shapviz_0.9.6.zip, r-oldrel: shapviz_0.9.6.zip
macOS binaries: r-release (arm64): shapviz_0.9.6.tgz, r-oldrel (arm64): shapviz_0.9.6.tgz, r-release (x86_64): shapviz_0.9.6.tgz, r-oldrel (x86_64): shapviz_0.9.6.tgz
Old sources: shapviz archive

Reverse dependencies:

Reverse suggests: fastshap, flowml

Linking:

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