Introducing class-based classification priority in fuzzy rule-based classification systems

Tomoharu Nakashima*, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we propose a fuzzy rule-generation method for pattern classification problems with classification priority. The assumption in this paper is that a classification priority is given a priori in relation to other classes. Our fuzzy rule-based classification system consists of a set of fuzzy ifthen rules that are automatically generated from a set of given training patterns. The proposed method decides the consequent class of fuzzy if-then rules based on the number of covered training patterns for each class. In computational experiments we first show the effect of introducing classification priority for a synthetic two-dimensional problem. Then we show the effectiveness of the proposed method for several real-world pattern classification problems.

Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
PublisherIEEE
ISBN (Print)1424412102, 9781424412105
DOIs
Publication statusPublished - 1 Dec 2007
Event2007 IEEE International Conference on Fuzzy Systems, FUZZY - London, United Kingdom
Duration: 23 Jul 200726 Jul 2007

Conference

Conference2007 IEEE International Conference on Fuzzy Systems, FUZZY
CountryUnited Kingdom
CityLondon
Period23/07/0726/07/07

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    Nakashima, T., Yokota, Y., Schaefer, G., & Ishibuchi, H. (2007). Introducing class-based classification priority in fuzzy rule-based classification systems. In IEEE International Conference on Fuzzy Systems [4295632] IEEE. https://doi.org/10.1109/FUZZY.2007.4295632