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  "Description": "Efficient implementation of Kernel SHAP (Lundberg and Lee,\n2017, <doi:10.48550/arXiv.1705.07874>) permutation SHAP, and\nadditive SHAP for model interpretability.  For Kernel SHAP and\npermutation SHAP, if the number of features is too large for\nexact calculations, the algorithms iterate until the SHAP\nvalues are sufficiently precise in terms of their standard\nerrors.  The package integrates smoothly with meta-learning\npackages such as 'tidymodels', 'caret' or 'mlr3'. It supports\nmulti-output models, case weights, and parallel computations.\nVisualizations can be done using the R package 'shapviz'.",
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  "Date/Publication": "2025-09-20 15:48:08 UTC",
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