Package: kernelshap
Title: Kernel SHAP
Version: 0.3.1
Authors@R: c(
    person("Michael", "Mayer", , "mayermichael79@gmail.com", role = c("aut", "cre")),
    person("David", "Watson", , "david.s.watson11@gmail.com", role = "ctb")
  )
Description: Multidimensional refinement of the Kernel SHAP algorithm
    described in Ian Covert and Su-In Lee (2021)
    <http://proceedings.mlr.press/v130/covert21a>.  The package allows to
    calculate Kernel SHAP values in an exact way, by iterative sampling
    (as in the reference above), or by a hybrid of the two.  As soon as
    sampling is involved, the algorithm iterates until convergence, and
    standard errors are provided.  The package works with any model that
    provides numeric predictions of dimension one or higher.  Examples
    include linear regression, logistic regression (on logit or
    probability scale), other generalized linear models, generalized
    additive models, and neural networks.  The package plays well together
    with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'.
    Visualizations can be done using the R package 'shapviz'.
License: GPL (>= 2)
Depends: R (>= 3.2.0)
Encoding: UTF-8
RoxygenNote: 7.2.1
Imports: doRNG, foreach, MASS, stats, utils
Suggests: doFuture, testthat (>= 3.0.0)
Config/testthat/edition: 3
URL: https://github.com/mayer79/kernelshap
BugReports: https://github.com/mayer79/kernelshap/issues
NeedsCompilation: no
Packaged: 2022-11-18 13:04:30 UTC; Michael
Author: Michael Mayer [aut, cre],
  David Watson [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-18 13:40:02 UTC
