Cookies?
Library Header Image
LSE Research Online LSE Library Services

Robust reductions from ranking to classification

Balcan, Maria-Florina, Bansal, Nikhil, Beygelzimer, Alina , Coppersmith, Don , Langford, John and Sorkin, Gregory B. (2008) Robust reductions from ranking to classification. Machine Learning, 72 (1-2). pp. 139-153. ISSN 0885-6125

Full text not available from this repository.

Abstract

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.

Item Type: Article
Official URL: http://www.springerlink.com/content/100309/
Additional Information: © 2008 Springer Science+Business Media, LLC
Library of Congress subject classification: Q Science > QA Mathematics
Sets: Research centres and groups > Management Science Group
Departments > Management
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 13 Apr 2011 10:52
URL: http://eprints.lse.ac.uk/35410/

Actions (login required)

Record administration - authorised staff only Record administration - authorised staff only