what is roc curve in machine learning

An ROC (Receiver Operating Characteristic) curve is a graphical plot that illustrates the performance of a binary classifier model at varying classification thresholds. It shows the trade-off between the true positive rate (TPR) and the false positive rate (FPR) as the discrimination threshold is varied. The AUC (Area Under the Curve) measures the entire two-dimensional area underneath the entire ROC curve and provides an aggregate measure of performance across all possible classification thresholds. A higher AUC value indicates better classifier performance