Dynamic Classifier Aggregation Using Fuzzy t-conorm Integral

Fuzzy integral is a general aggregation operator,which encompasses many common aggregation operators like weighted mean, ordered weighted mean, weighted minimum and maximum, etc. In classifier combining, it can be usedto aggregate the outputs of the individual classifiers in the team with respect to a fuzzy measure, based on the classifier confidences. In practice, the Choquet integral and the Sugeno integral are used most often. However, they both belong tothe more general family of fuzzy t-conorm integral. In this paper, we theoretically examine which fuzzy t-conorm integrals are useful for classifier aggregation, and we experimentally compare the individual methods on 23 benchmark datasets.