AUC

AUC, or Area Under the Curve, is a performance measurement for classification problems at various threshold settings. It represents the degree or measure of separability achieved by a model, indicating how well the model can distinguish between classes. The AUC value ranges from 0 to 1, where a value of 0.5 suggests no discriminative ability, while a value of 1 indicates perfect classification. AUC is commonly used in conjunction with Receiver Operating Characteristic (ROC) curves to evaluate the performance of binary classifiers. It is particularly useful in scenarios where the classes are imbalanced, providing a single metric to summarize model performance across all classification thresholds.