Title :
Rough Neuro-Fuzzy Structures for Classification With Missing Data
Author_Institution :
Dept. of Comput. Eng., Czestochowa Univ. of Technol., Czestochowa, Poland
Abstract :
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.
Keywords :
fuzzy neural nets; fuzzy set theory; pattern classification; rough set theory; Mamdani-type neuro-fuzzy structure; missing data; rough fuzzy sets; rough neuro-fuzzy classifier; Classification; fuzzy sets; missing data; neuro-fuzzy architectures; rough sets;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2009.2012504
