Meta-Typicalness Approach to Reliable Classification

Authors:
E. N. Smirnov;S. Vanderlooy;I. G. Sprinkhuizen-Kuyper
Affiliations:
MICC-IKAT, Universiteit Maastricht, Maastricht 6200 MD, The Netherlands, email: {smirnov, kuyper, s.vanderlooy}@cs.unimaas.nl;MICC-IKAT, Universiteit Maastricht, Maastricht 6200 MD, The Netherlands, email: {smirnov, kuyper, s.vanderlooy}@cs.unimaas.nl;MICC-IKAT, Universiteit Maastricht, Maastricht 6200 MD, The Netherlands, email: {smirnov, kuyper, s.vanderlooy}@cs.unimaas.nl
Venue:
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Year:
2006

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Abstract

We propose a meta-typicalness approach to apply the typicalness framework for any type of classifiers. The approach can be used to construct classifiers with specified classification performance. Experiments show that the approach results in classifiers that can outperform an existing typicalness-based classifier.