What is the significance of the ROC curve in classification tasks?

The Receiver Operating Characteristic (ROC) curve plots the true positive rate (TPR) against the false positive rate (FPR) at various thresholds. It helps evaluate the performance of classification models. The AUC (Area Under the Curve) score is a summary measure of the model’s ability to distinguish between classes.