Machine Learning, Heartbeat.
versus the false positive rate (FPR) at different classification thresholds. It provides a way to balance the trade-off between sensitivity (TPR) and specificity (1 — FPR) for different classification thresholds. The AUC (area under the curve) summarizes the model's overall performance across all