From ensemble of fuzzy classifiers to single fuzzy rule base classifier

Abstract

Neuro-fuzzy systems show very good performance and the knowledge comprised within their structure is easily interpretable. To further improve their accuracy they can be combined into ensembles. In the paper we combine specially modified Mamdani neuro-fuzzy systems into an AdaBoost ensemble. The proposed modification improves the interpretability of knowledge by allowing merging the subsystems rule bases into one knowledge base. Simulations on two benchmarks shows excellent performance of the modified neuro-fuzzy systems. © 2008 Springer-Verlag Berlin Heidelberg.