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An Application of OWA Operators to the Aggregation of Multiple Classification Decisions

In: The Ordered Weighted Averaging Operators

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  • Ludmila I. Kuncheva

    (Imperial College, Department of Electrical and Electronic Engineering)

Abstract

The paper considers a classification scheme made up by pooling together multiple classifiers and aggregating their decisions. The individual decisions are treated as degrees of membership assigned by the classifier to the object to be classified. We are interested in how the OWA operators compare to simple voting, linear and logarithmic techniques. In general, all the aggregation schemes appear to be of the same quality, superior to the single classifiers. It was found that OWA operators tend to generalize better than their competitors when the individual classifiers are overtrained. The idea is illustrated on a real and on an artificial data set.

Suggested Citation

  • Ludmila I. Kuncheva, 1997. "An Application of OWA Operators to the Aggregation of Multiple Classification Decisions," Springer Books, in: Ronald R. Yager & Janusz Kacprzyk (ed.), The Ordered Weighted Averaging Operators, pages 330-343, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4615-6123-1_25
    DOI: 10.1007/978-1-4615-6123-1_25
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