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.domain | compute and plot weighted mean SHAP contributions at group level (factors or domains) |
hmda.efa | Perform Exploratory Factor Analysis with HMDA |
hmda.feature.selection | Feature Selection Based on Weighted SHAP Values |
hmda.grid | Tune Hyperparameter Grid for HMDA Framework |
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.search.param | Search for Hyperparameters via Random Search |
hmda.suggest.param | Suggest Hyperparameters for tuning HMDA Grids |
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 |
list_hyperparameter | Create Hyperparameter List from a leaderboard dataset |
suggest_mtries | Suggest Alternative mtries Values |