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

AuthorAlicja Gosiewska [aut, cre], Przemyslaw Biecek [aut], Michal Burdukiewicz [ctb]
MaintainerAlicja Gosiewska <[email protected]>
Package repositoryView on CRAN
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shapper documentation built on May 1, 2019, 9:19 p.m.