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Robust reductions from ranking to classification

By Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford and Gregory B. Sorkin


We reduce ranking, as measured by the Area Under the Receiver Operating Characteristic Curve (AUC), to binary classification. The core theorem shows that a binary classification regret of r on the induced binary problem implies an AUC regret of at most 2r. This is a large improvement over approaches such as ordering according to regressed scores, which have a regret transform of r ↦ nr where n is the number of elements

Topics: QA Mathematics
Publisher: Springer
Year: 2008
DOI identifier: 10.1007/s10994-008-5058-6
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Provided by: LSE Research Online
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