R: Weighted Mean SHAP and CI for Robust Feature Assessment in ML Grid

# Weighted Mean SHAP and CI for Robust Feature Assessment in ML Grid

## Documentation for package ‘shapley’ version 0.7.0

- DESCRIPTION file
- Package README

## Help Pages

feature.selection | Select top features by weighted mean SHAP (WMSHAP)
feature.test | Weighted permutation test for paired difference of means
h2o.get_ids | Extract model IDs from H2O AutoML or Grid objects
normalize | Normalize a vector based on specified minimum and maximum values
shapley | Weighted Mean SHAP (WMSHAP) and Confidence Interval for Multiple Models (tuning grid, stacked ensemble, etc.)
shapley.domain | Compute and plot weighted mean SHAP contributions at group level (factors or domains)
shapley.domain.test | Weighted permutation test for difference between two domains
shapley.feature.test | Weighted permutation test for WMSHAP difference between two features
shapley.plot | Plot weighted mean SHAP (WMSHAP) contributions
shapley.row.plot | WMSHAP row-level plot for a single observation (participant or data row)
shapley.table | Create WMSHAP Summary Table Based on the Given Criterion
shapley.top | Flag and rank features by WMSHAP cutoffs