# Automated Multi-Outcome Machine Learning Combination Models

## Documentation for package ‘AutoMLR’ version 1.0.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

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.
binarymlr_parameters | Default parameters for AutoMLR binary-classification workflows.
binary_auc | ROC AUC for binary outcomes.
binary_pr_auc | Precision-recall AUC for binary outcomes.
check_automlr_dependencies | Check optional AutoMLR model backends and feature dependencies.
continuousmlr_parameters | Default parameters for AutoMLR continuous-outcome workflows.
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.
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_algorithms_loocv | Evaluate multiple survival model variants by LOOCV C-index.
evaluate_algorithm_loocv | Run LOOCV for a named algorithm in the registry.
evaluate_binary_algorithms_loocv | Evaluate binary model variants by LOOCV AUC.
evaluate_binary_algorithm_loocv | Evaluate one binary algorithm 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.
ordinalmlr_parameters | Default parameters for AutoMLR ordinal-outcome workflows.
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.
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