Using Two-Class Classifiers for Multiclass Classification

Conference paper (2002)

Authors

D.M.J. Tax ImPhys/Quantitative Imaging
R.P.W. Duin ImPhys/Quantitative Imaging
Research Group
ImPhys/Quantitative Imaging
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Published Date

2002

Language

Undefined/Unknown

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Research Group

ImPhys/Quantitative Imaging

Abstract

The generalization from two-class classification to multiclass classification is not straightforward for discriminants which are not based on density estimation. Simple combining methods use voting, but this has the drawback of inconsequent labelings and ties. More advanced methods map the discriminant outputs to approximate posterior probability estimates and combine these, while other methods use error-correcting output codes. In this paper we want to show the possibilities of simple generalizations of the twoclass classification, using voting and combinations of approximate posterior probabilities.