Automated Multi-Outcome Machine Learning Combination Models

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Documentation for package ‘AutoMLR’ version 1.0.0

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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