automlr_input_to_binary_xy
                        Extract modeling matrices from prepared binary
                        input.
automlr_input_to_continuous_xy
                        Extract modeling matrices from prepared
                        continuous input.
automlr_input_to_ordinal_xy
                        Extract modeling matrices from prepared ordinal
                        input.
automlr_input_to_surv_xy
                        Extract modeling matrices from prepared
                        survival input.
automlr_parameters      Default parameters for AutoMLR survival
                        pipeline.
binary_auc              ROC AUC for binary outcomes.
binary_pr_auc           Precision-recall AUC for binary outcomes.
binarymlr_parameters    Default parameters for AutoMLR
                        binary-classification workflows.
check_automlr_dependencies
                        Check optional AutoMLR model backends and
                        feature dependencies.
continuous_cor          Correlation between observed and predicted
                        continuous outcomes.
continuous_mae          Mean absolute error for continuous predictions.
continuous_r2           Coefficient of determination for continuous
                        predictions.
continuous_rmse         Root mean squared error for continuous
                        predictions.
continuousmlr_parameters
                        Default parameters for AutoMLR
                        continuous-outcome workflows.
count_binary_combinations
                        Count binary model combinations without
                        fitting.
count_continuous_combinations
                        Count continuous model combinations without
                        fitting.
count_ordinal_combinations
                        Count ordinal model combinations without
                        fitting.
count_surv_combinations
                        Count model combinations without fitting
                        models.
disable_auto_logging    Disable AutoMLR auto logging.
evaluate_algorithm_loocv
                        Run LOOCV for a named algorithm in the
                        registry.
evaluate_algorithms_loocv
                        Evaluate multiple survival model variants by
                        LOOCV C-index.
evaluate_binary_algorithm_loocv
                        Evaluate one binary algorithm by LOOCV AUC.
evaluate_binary_algorithms_loocv
                        Evaluate binary model variants by LOOCV AUC.
evaluate_binary_combinations
                        Evaluate all-subset binary probability
                        combinations.
evaluate_continuous_algorithm
                        Evaluate one continuous algorithm by
                        out-of-fold performance.
evaluate_continuous_algorithms
                        Evaluate continuous model variants by
                        out-of-fold performance.
evaluate_continuous_combinations
                        Evaluate all-subset continuous prediction
                        combinations.
evaluate_ordinal_algorithms
                        Evaluate ordinal model variants by out-of-fold
                        performance.
evaluate_ordinal_combinations
                        Evaluate all-subset ordinal score combinations.
evaluate_surv_combinations
                        Evaluate all-subset survival model
                        combinations.
export_binary_results   Export binary AutoMLR results.
export_continuous_results
                        Export continuous AutoMLR results.
export_extreme_screen_results
                        Export extreme-screening tables and
                        publication-style audit figures
export_ordinal_results
                        Export ordinal AutoMLR results.
export_surv_results     Export AutoMLR survival results as a
                        reproducible result bundle.
extreme_surv_screen     Extreme two-stage screening for survival model
                        combinations
fit_binary_ensemble     Fit a binary probability ensemble.
fit_continuous_ensemble
                        Fit a continuous-outcome prediction ensemble.
fit_ordinal_ensemble    Fit an ordinal-outcome ensemble.
fit_surv_ensemble       Fit a weighted ensemble of survival-risk
                        models.
get_binary_registry     Return the binary-classification algorithm
                        registry.
get_continuous_registry
                        Return the continuous-outcome algorithm
                        registry.
get_ordinal_registry    Return the ordinal-outcome algorithm registry.
get_surv_registry       Return the full survival-algorithm registry.
initialize_auto_logging
                        Enable file + console logging for the current R
                        session.
list_binary_algorithms
                        List supported binary-classification
                        algorithms.
list_binary_model_variants
                        List binary-classification model variants.
list_continuous_algorithms
                        List supported continuous-outcome algorithms.
list_continuous_model_variants
                        List continuous-outcome model variants.
list_model_variants     List concrete model variants generated from
                        algorithm grids.
list_ordinal_algorithms
                        List supported ordinal-outcome algorithms.
list_ordinal_model_variants
                        List ordinal-outcome model variants.
list_surv_algorithms    List the supported survival algorithms (keys).
loocv_auc               Leave-one-out cross-validation AUC for one
                        binary algorithm.
loocv_cindex            Leave-one-out cross-validation C-index for one
                        survival algorithm.
ordinal_accuracy        Accuracy for ordinal class predictions.
ordinal_balanced_accuracy
                        Balanced accuracy for ordinal class
                        predictions.
ordinal_mae             Mean absolute class error for ordinal
                        predictions.
ordinal_qwk             Quadratic weighted kappa for ordinal
                        predictions.
ordinalmlr_parameters   Default parameters for AutoMLR ordinal-outcome
                        workflows.
parallel_lapply         Parallel 'lapply' that transparently falls back
                        to sequential.
predict.automlr_binary_ensemble
                        Predict binary ensemble probabilities or
                        classes.
predict.automlr_continuous_ensemble
                        Predict continuous ensemble values.
predict.automlr_ordinal_ensemble
                        Predict ordinal ensemble scores or classes.
predict.automlr_surv_ensemble
                        Predict weighted ensemble risk.
prepare_binary_cohort_input
                        Prepare multi-cohort binary-classification
                        data.
prepare_cohort_input    Prepare multi-cohort survival data from a
                        single long-format table.
prepare_continuous_cohort_input
                        Prepare multi-cohort continuous-outcome data.
prepare_ordinal_cohort_input
                        Prepare multi-cohort ordinal-outcome data.
print.automlr_dependency_report
                        Print an AutoMLR dependency report.
print.automlr_extreme_screen
                        Print method for extreme survival screening
recommend_binary_auc_threshold
                        Recommend a binary AUC cutoff from candidate
                        model results.
recommend_continuous_r2_threshold
                        Recommend a continuous R-squared cutoff from
                        candidate model results.
recommend_ordinal_qwk_threshold
                        Recommend an ordinal kappa cutoff from
                        candidate model results.
recommend_surv_cindex_threshold
                        Recommend a survival C-index cutoff from
                        candidate model results.
render_binary_report    Render an HTML report for a fitted binary
                        ensemble.
render_continuous_report
                        Render an HTML report for a fitted continuous
                        ensemble.
render_ordinal_report   Render an HTML report for a fitted ordinal
                        ensemble.
render_surv_report      Render an HTML report for a fitted survival
                        ensemble.
report_binary_cohort_intersection
                        Print a binary cohort-intersection report.
report_cohort_intersection
                        Print a human-readable report of the cohort
                        intersection.
report_continuous_cohort_intersection
                        Print a continuous cohort-intersection report.
report_ordinal_cohort_intersection
                        Print an ordinal cohort-intersection report.
start_parallel          Start the parallel backend.
stop_parallel           Stop the parallel backend.
summarize_base_models   Summarize base-model screening results in
                        Markdown
summarize_binary_analysis_results
                        Summarize a complete binary AutoMLR analysis in
                        Markdown.
summarize_binary_base_models
                        Summarize binary base-model screening in
                        Markdown.
summarize_binary_data_preparation
                        Summarize binary data preparation in Markdown.
summarize_binary_ensemble_results
                        Summarize binary ensemble selection in
                        Markdown.
summarize_binary_explainability_results
                        Summarize binary explainability outputs in
                        Markdown.
summarize_data_preparation
                        Summarize data-preparation results in Markdown
summarize_ensemble_results
                        Summarize ensemble-selection results in
                        Markdown
summarize_explainability_results
                        Summarize explainability and clinical-utility
                        outputs in Markdown
summarize_extreme_screen_results
                        Summarize extreme-screening results in readable
                        Markdown
summarize_surv_analysis_results
                        Summarize a complete regular survival AutoML
                        analysis in Markdown
