Package: shapper 0.1.4

Szymon Maksymiuk

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'.

Authors:Szymon Maksymiuk [aut, cre], Alicja Gosiewska [aut], Przemyslaw Biecek [aut], Mateusz Staniak [ctb], Michal Burdukiewicz [ctb]

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shapper.pdf |shapper.html✨
shapper/json (API)
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Peer review:

Bug tracker:https://github.com/modeloriented/shapper/issues

On CRAN:

4 exports 58 stars 3.42 score 44 dependencies 49 scripts 499 downloads

Last updated 1 years agofrom:3b54449553. Checks:OK: 7. Indexed: yes.

Exports:individual_variable_effectinstall_shapshaptheme_drwhy_colors

Dependencies:clicodetoolscolorspaceDALEXfansifarverforeachggplot2gluegridExtragtablehereiBreakDowningredientsisobanditeratorsjsonlitekernelshaplabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpngR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootscalestibbleutf8vctrsviridisLitewithr