Area Under Curve (AUC)

The Area Under the Curve (AUC) is a measure used to evaluate the performance of a classification model, especially in binary classification tasks. It assesses how well the model distinguishes between two classes (e.g., positive vs. negative cases). The "curve" refers to the Receiver Operating Characteristic (ROC) curve, which plots true positive rate against false positive rate at various thresholds. The AUC value ranges from 0.5 (no better than random guessing) to 1 (perfect discrimination). A higher AUC indicates a better model at ranking and separating different classes effectively.