Modular rough neuro-fuzzy systems for classification

Authors:
Rafał Scherer;Marcin Korytkowski;Robert Nowicki;Leszek Rutkowski
Affiliations:
Department of Computer Engineering, Czçstochowa University of Technology, Człstochowa, Poland and Department of Artificial Intelligence, Academy of Humanities and Economics in Lodz, ...;Department of Computer Engineering, Czçstochowa University of Technology, Człstochowa, Poland and Olsztyn Academy of Computer Science and Management, Olsztyn, Poland;Department of Computer Engineering, Czçstochowa University of Technology, Człstochowa, Poland and Department of Artificial Intelligence, Academy of Humanities and Economics in Lodz, ...;Department of Computer Engineering, Czçstochowa University of Technology, Człstochowa, Poland and Department of Artificial Intelligence, Academy of Humanities and Economics in Lodz, ...
Venue:
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Year:
2007

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Abstract

In the paper we propose a new class of modular systems for classification in the case of missing features. We incorporate the rough set theory into construction of neuro-fuzzy systems which create the modular structure. The AdaBoost algorithm is combined with the gradient algorithm to train the whole system. We illustrate the performance of our approach on typical benchmarks.