Title :
Rule Weight Specification in Fuzzy Rule-Based Classification Systems
Author :
Ishibuchi, Hisao ; Yamamoto, Takashi
Author_Institution :
Dept. of Ind. Eng., Osaka Prefecture Univ., Japan
Abstract :
This paper shows how the rule weight of each fuzzy rule can be specified in fuzzy rule-based classification systems. First, we propose two heuristic methods for rule weight specification. Next, the proposed methods are compared with existing ones through computer simulations on artificial numerical examples and real-world pattern classification problems. Simulation results show that the proposed methods outperform the existing ones in the case of multiclass pattern classification problems with many classes.
Keywords :
data mining; fuzzy reasoning; fuzzy set theory; knowledge based systems; pattern classification; data mining; fuzzy rule based classification system; heuristic method; multiclass pattern classification; rule weight specification; Association rules; Computational modeling; Computer simulation; Data mining; Degradation; Fuzzy sets; Fuzzy systems; Industrial engineering; Knowledge based systems; Pattern classification; Data mining; fuzzy systems; pattern classification; rule generation; rule selection;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2004.841738
