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Rough Neuro-Fuzzy Structures for Classification With Missing Data

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1 Author(s)
Nowicki, R. ; Dept. of Comput. Eng., Czestochowa Univ. of Technol., Czestochowa, Poland

This paper presents a new approach to fuzzy classification in the case of missing data. The rough fuzzy sets are incorporated into Mamdani-type neuro-fuzzy structures, and the rough neuro-fuzzy classifier is derived. Theorems that allow the determination of the structure of a rough neuro-fuzzy classifier are given. Several experiments illustrating the performance of the rough neuro-fuzzy classifier working in the case of missing features are described.

Published in:

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:39 ,  Issue: 6 )

Date of Publication:

Dec. 2009

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