A Fuzzy Reasoning Method Based on Ensembles of Generalizations of the Choquet Integral

Abstract

An efficient way to deal with classification problems is by using Fuzzy Rule-Based Classification Systems. A key point in this kind of classifier is the Fuzzy Reasoning Method (FRM). This mechanism is responsible for performing the classification of examples into predefined classes. There are different generalizations of the Choquet integral in the literature that are applied in the FRM. This paper presents an initial study of a new FRM that is ensemble-based, which combines different generalizations in a more effective final classifier. We have constructed two distinct ensemble decision-making methods considering the majority and weighted voting approaches. The experimental results demonstrate that the performance of the proposed methods is statistically equivalent compared to the state-of-art generalizations.