Boosting ensemble of relational neuro-fuzzy systems

Authors:
Rafał Scherer
Affiliations:
Department of Computer Engineering, Częstochowa University of Technology, Częstochowa, Poland
Venue:
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 16
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Abstract

In the paper a boosting ensemble of neuro-fuzzy relational systems is created. Rules in relational fuzzy systems are more flexible than rules in linguistic fuzzy systems because of the additional weights in rule consequents. The weights come from an additional binary relation. Thanks to this, input and output fuzzy sets are related to each other with a certain degree. The size of the relations is determined by the number of input fuzzy sets and the number of output fuzzy sets. Simulations performed on popular benchmarks show that the proposed ensemble outperforms other learning systems.