By Topic

Rough Neuro-Fuzzy Structures for Classification With Missing Data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

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 )