What is the difference between accuracy and ROC-AUC?

Accuracy measures correct predictions, while ROC-AUC measures ranking quality across thresholds.

Accuracy is threshold-dependent and can be misleading in imbalanced datasets. ROC-AUC evaluates model ability to distinguish classes across all thresholds, plotting true positive rate vs false positive rate.