Extending ROC Analysis to Uncertainty-Aware Risk Prediction with an Interval-Based AUC (iAUC)
The paper develops an uncertainty-aware framework to evaluate interval-valued risk predictions, moving beyond standard ROC curves. It introduces two metrics, AUCL and AUCU, which quantify ranking performance based on interval overlap and strictness. This allows practitioners to understand how predictive uncertainty affects discrimination and enables selective prediction strategies.