On the explicit use of example weights in the construction of classifiers

Authors:
Andrew Naish-Guzman;Sean Holden;Ulrich Paquet
Affiliations:
Computer Laboratory, University of Cambridge, Cambridge, UK;Computer Laboratory, University of Cambridge, Cambridge, UK;Computer Laboratory, University of Cambridge, Cambridge, UK
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

We present a novel approach to two-class classification, in which a classifier is parameterised in terms of a distribution over examples. The optimal distribution is determined by the solution of a linear program; it is found experimentally to be highly sparse, and to yield a classifier resistant to noise whose error rates are competitive with the best existing methods.