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Sample width for multi-category classifiers

Anthony, Martin and Ratsaby, Joel (2012) Sample width for multi-category classifiers. RUTCOR Research Reports, RRR 29-2012. RUTCOR, Rutgers University, Piscataway, New Jersey, USA.

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Abstract

In a recent paper, the authors introduced the notion of sample width for binary classifiers defined on the set of real numbers. It was shown that the performance of such classifiers could be quantified in terms of this sample width. This paper considers how to adapt the idea of sample width so that it can be applied in cases where the classifiers are multi-category and are defined on some arbitrary metric space.

Item Type: Monograph (Technical Report)
Official URL: http://rutcor.rutgers.edu/
Additional Information: © 2012 Rutgers, The State University of New Jersey
Library of Congress subject classification: Q Science > QA Mathematics
Sets: Departments > Mathematics
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Identification Number: RRR 29-2012
Funders: IST Programme of the European Community, PASCAL2 Network of Excellence
Date Deposited: 29 Nov 2012 14:39
URL: http://eprints.lse.ac.uk/47543/

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