Package: shapviz
Title: SHAP Visualizations
Version: 0.10.4
Authors@R: c(
    person("Michael", "Mayer", , "mayermichael79@gmail.com", role = c("aut", "cre")),
    person("Adrian", "Stando", , "adrian.j.stando@gmail.com", role = "ctb")
  )
Description: 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.
License: GPL (>= 2)
Depends: R (>= 3.6.0)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
Imports: ggfittext (>= 0.8.0), gggenes, ggplot2 (>= 3.5.2), ggrepel,
        grid, patchwork (>= 1.3.0), rlang (>= 0.3.0), stats, utils,
        xgboost
Enhances: h2o, lightgbm
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://github.com/ModelOriented/shapviz,
        https://modeloriented.github.io/shapviz/
BugReports: https://github.com/ModelOriented/shapviz/issues
Config/roxygen2/version: 8.1.0
Config/pak/sysreqs: make libicu-dev libjpeg-dev libpng-dev libxml2-dev
        libssl-dev
Repository: https://modeloriented.r-universe.dev
Date/Publication: 2026-08-31 16:36:25 UTC
RemoteUrl: https://github.com/modeloriented/shapviz
RemoteRef: HEAD
RemoteSha: a3ead2491c66b7345eaf23e212eb1edda03b4697
NeedsCompilation: no
Packaged: 2026-10-08 12:23:40 UTC; root
Author: Michael Mayer [aut, cre],
  Adrian Stando [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>
