David Stefka

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Fuzzy integral is a general aggregation operator,which encompasses many common aggregation operators likeweighted mean, ordered weighted mean, weighted minimumand maximum, etc. In classifier combining, it can be usedto aggregate the outputs of the individual classifiers in theteam with respect to a fuzzy measure, based on the classifierconfidences. In(More)
The paper deals with the aggregation of classification rules by means of fuzzy integrals, in particular with the fuzzy measures employed in that aggregation. It points out that the kinds of fuzzy measures commonly encountered in this context do not take into account the diversity of classification rules. As a remedy, a new kind of fuzzy measures is(More)
In classifier combining, predictions of several classifiers are aggregated into a single prediction in order to improve the classification quality. Among others, fuzzy integrals are commonly used as aggregation operators. Usually, Sugeno lambda-measure is used as the fuzzy measure of the integral. However, interaction between the classifiers in the team(More)
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