Package: shapper
Title: Wrapper of Python Library 'shap'
Version: 0.1.4
Authors@R: c(
  person("Szymon", "Maksymiuk", email = "sz.maksymiuk@gmail.com", role = c("aut", "cre")),
  person("Alicja", "Gosiewska", email = "alicjagosiewska@gmail.com", role = c("aut")),
  person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut")),
  person("Mateusz", "Staniak", role = c("ctb")),
  person("Michal", "Burdukiewicz", email = "michalburdukiewicz@gmail.com", role = c("ctb"))
  )
Description: 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) <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'.
License: GPL
Encoding: UTF-8
URL: https://github.com/ModelOriented/shapper
BugReports: https://github.com/ModelOriented/shapper/issues
RoxygenNote: 7.2.3
Imports: reticulate, DALEX, ggplot2
Suggests: covr, knitr, randomForest, rpart, testthat, markdown, qpdf
VignetteBuilder: knitr
Config/pak/sysreqs: libpng-dev python3
Repository: https://modeloriented.r-universe.dev
Date/Publication: 2023-05-25 01:42:27 UTC
RemoteUrl: https://github.com/modeloriented/shapper
RemoteRef: HEAD
RemoteSha: 3b54449553210c53cde323ef9a0ddbfc91f8bea5
NeedsCompilation: no
Packaged: 2026-07-15 13:33:11 UTC; root
Author: Szymon Maksymiuk [aut, cre],
  Alicja Gosiewska [aut],
  Przemyslaw Biecek [aut],
  Mateusz Staniak [ctb],
  Michal Burdukiewicz [ctb]
Maintainer: Szymon Maksymiuk <sz.maksymiuk@gmail.com>