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The area under curve (AUC) statistic is an empirical measure of classification performance based on the area under an ROC curve. It evaluates the performance of a scoring classifier on a test set, but ignores the magnitude of the scores and only takes their rank order into account. AUC is expressed on a scale of 0 to 1, where 0 means that all negatives are ranked before all positives, and 1 means that all positives are ranked before all negatives. See ROC Analysis.
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(2017). Area Under Curve. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_918
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_918
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