best_of_family          Select Best Models by Performance Metrics
check_efa               Check Exploratory Factor Analysis Suitability
dictionary              Dictionary of Variable Attributes
hmda.adjust.params      Adjust Hyperparameter Combinations
hmda.autoEnsemble       Build Stacked Ensemble Model Using autoEnsemble
                        R package
hmda.best.models        Select Best Models Across All Models in HMDA
                        Grid
hmda.compare.shap.plot
                        Compare SHAP plots across selected models
hmda.domain             Domain-level WMSHAP summary and plot
hmda.efa                Perform Exploratory Factor Analysis with HMDA
hmda.feature.selection
                        Feature Selection Based on Weighted SHAP Values
hmda.grid               Tune a Cartesian Hyperparameter Grid in HMDA
hmda.grid.analysis      Analyze Hyperparameter Grid Performance
hmda.init               Initialize or Restart H2O Cluster for HMDA
                        Analysis
hmda.partition          Partition Data for HMDA Analysis
hmda.plot               Plot WMSHAP contributions
hmda.plot.metrics       Plot model performance metrics across a grid of
                        models
hmda.row.plot           WMSHAP row-level plot for a single observation
                        (participant or data row)
hmda.search.param       Search for Hyperparameters via Random Search
hmda.suggest.param      Suggest Hyperparameters for tuning HMDA Grids
hmda.test               Normalize a vector based on specified minimum
                        and maximum values
hmda.wmshap             Compute Weighted Mean SHAP Values and
                        Confidence Intervals via shapley algorithm
hmda.wmshap.table       Create SHAP Summary Table Based on the Given
                        Criterion
suggest_mtries          Suggest Alternative mtries Values
