AUC

AUC stands for Area Under the Curve, commonly used in evaluating the performance of binary classification models. Imagine plotting a graph where the x-axis represents the false positive rate and the y-axis represents the true positive rate. The AUC measures the area under the curve of this graph. An AUC of 1 indicates perfect accuracy, while an AUC of 0.5 suggests the model is no better than random guessing. Essentially, a higher AUC value indicates a better-performing model, as it effectively distinguishes between the two classes it is trying to classify.