On the Combination of Locally Optimal Pairwise Classifiers

Authors:
Gero Szepannek;Bernd Bischl;Claus Weihs
Affiliations:
Department of Statistics, University of Dortmund, 44227 Dortmund,;Department of Statistics, University of Dortmund, 44227 Dortmund,;Department of Statistics, University of Dortmund, 44227 Dortmund,
Venue:
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2007

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Abstract

If their assumptions are not met, classifiers may fail. In this paper, the possibility of combining classifiers in multi-class problems is investigated. Multi-class classification problems are split into two class problems. For each of the latter problems an optimal classifier is determined. The results of applying the optimal classifiers on the two class problems can be combined using the Pairwise Couplingalgorithm by Hastie and Tibshirani (1998).In this paper exemplary situations are investigated where the respective assumptions of Naive Bayes or the classical Linear Discriminant Analysis (LDA, Fisher, 1936) fail. It is investigated at which degree of violations of the assumptions it may be advantageous to use single methods or a classifier combination by Pairwise Coupling.