Efficient implementation of Kernel SHAP, see Lundberg and Lee (2017), and Covert and Lee (2021) <http://proceedings.mlr.press/v130/covert21a>. For models with up to eight features, the results are exact regarding the selected background data. Otherwise, an almost exact hybrid algorithm involving iterative sampling is used. The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'. Visualizations can be done using the R package 'shapviz'.
To install this package, run one of the following:
Summary
Efficient implementation of Kernel SHAP, see Lundberg and Lee (2017), and Covert and Lee (2021) <http://proceedings.mlr.press/v130/covert21a>. For models with up to eight features, the results are exact regarding the selected background data. Otherwise, an almost exact hybrid algorithm involving iterative sampling is used. The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'. Visualizations can be done using the R package 'shapviz'.
Information Last Updated
Apr 22, 2025 at 15:31
License
GPL-2
Total Downloads
39
Platforms