shapper: Wrapper of Python Library 'shap'

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'.

Package details

AuthorSzymon Maksymiuk [aut, cre], Alicja Gosiewska [aut], Przemyslaw Biecek [aut], Mateusz Staniak [ctb], Michal Burdukiewicz [ctb]
MaintainerSzymon Maksymiuk <sz.maksymiuk@gmail.com>
LicenseGPL
Version0.1.3
URL https://github.com/ModelOriented/shapper
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("shapper")

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shapper documentation built on Aug. 28, 2020, 9:08 a.m.