AUC (Area Under Curve)

AUC, or Area Under the Curve, is a metric used to evaluate the performance of a classification model, such as a spam filter or medical test. It measures how well the model can distinguish between different categories (like positive and negative cases). The "curve" refers to the Receiver Operating Characteristic (ROC) curve, which plots the true positive rate against the false positive rate at various thresholds. The AUC score summarizes this curve into a single number between 0 and 1. A higher AUC means the model is better at correctly identifying different classes, with 1 being perfect discrimination.