Wrapper of Python Library 'shap' R package shapper version 0.1.3 CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning) 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'. Software Imports: reticulate, DALEX, ggplot2 Suggests: covr, knitr, randomForest, rpart, testthat, markdown, qpdf Szymon Maksymiuk <sz.maksymiuk@gmail.com> Comprehensive R Archive Network (CRAN) Szymon Maksymiuk [aut, cre], Alicja Gosiewska [aut], Przemyslaw Biecek [aut], Mateusz Staniak [ctb], Michal Burdukiewicz [ctb] GPL 2020-08-28 application/tgz https://CRAN.R-project.org/package=shapper doi:10.32614/CRAN.package.shapper