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The ROC (Receiver Operating Characteristic) curve evaluates the performance of a classification model by plotting the rate of true positives against the rate of false positives. The AUC (Area Under the Curve) measures the area under this curve. The closer the AUC is to 1, the better the ability of the model to distinguish between classes.
