A fuzzy rule-based classification system using interval type-2 fuzzy sets

Authors:
Min Tang;Xia Chen;Weidong Hu;Wenxian Yu
Affiliations:
ATR Key Lab, National University of Defense Technology, Changsha, China;ATR Key Lab, National University of Defense Technology, Changsha, China;ATR Key Lab, National University of Defense Technology, Changsha, China;School of Electronic, Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China
Venue:
IUKM'11 Proceedings of the 2011 international conference on Integrated uncertainty in knowledge modelling and decision making
Year:
2011

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Abstract

The design of type-2 fuzzy rule-based classification systems from labeled data is considered in this study. With the aid of interval type-2 fuzzy sets, which can effectively capture uncertainties in the data, a compact and interpretable interval type-2 fuzzy rule base with fewer rules is constructed. Corresponding type-2 fuzzy reasoning method for classification is also presented. The validity of this classification system is shown through experimental results on several data sets.