A fuzzy fusion algorithm to combine multiple classifiers

Combining multiple classifiers is a natural way to discover useful information and improve the performances of individual classifiers. It´s based on the combination of the outputs of an ensemble of different classifiers. When interactions exist in combining multiple classifiers, fuzzy integral would be a valid method to fuse multiple classifiers. In this fuzzy fusion approach, the fuzzy measure plays an important role. Liu proposed a novel fuzzy measure, L-measure, which is more sensitive than some common measures, like ¿-measure, P-measure and V-measure. In this paper, we would combine the multiple classifiers by Choquet integral wtih this Z-measure.