Robust reductions from ranking to classification

Maria-Florina Balcan

doi:10.1007/s10994-008-5058-6

Robust reductions from ranking to classification

2008-04-26

32

OA

AI

DOI：10.1007/s10994-008-5058-6

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Abstract

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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 bar right arrow nr where n is the number of elements.

Keywords:

Ranking

Classification

Reductions

Robust reductions from ranking to classification

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