Robust reductions from ranking to classification

M.F. Balcan, N. Bansal, A. Beygelzimer, D. Coppersmith, J. Langford, G.B. Sorkin

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    37 Citaten (Scopus)


    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.
    Originele taal-2Engels
    Pagina's (van-tot)139-153
    TijdschriftMachine Learning
    Nummer van het tijdschrift1-2
    StatusGepubliceerd - 2008

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