Cognitive Computing in Business
AUC-ROC, which stands for Area Under the Curve - Receiver Operating Characteristic, is a performance measurement for classification models at various threshold settings. It combines the true positive rate and false positive rate into a single value that summarizes the model's ability to distinguish between classes. This metric is essential in evaluating model performance, particularly in situations with imbalanced classes, as it provides a clearer picture of how well a model can predict outcomes across different decision thresholds.
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