Reduced attribute oriented inconsistency handling in decision generation

Authors:
Yucai Feng;Wenhai Li;Zehua Lv;Xiaoming Ma
Affiliations:
Department of Computer Science, Huazhong University of Science and Technology, Wuhan, Hubei, China;Department of Computer Science, Huazhong University of Science and Technology, Wuhan, Hubei, China;Department of Computer Science, Huazhong University of Science and Technology, Wuhan, Hubei, China;Department of Computer Science, Huazhong University of Science and Technology, Wuhan, Hubei, China
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

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Abstract

Due to the discarded attributes, the effectual condition classes of the decision rules are highly different. To provide a unified evaluative measure, the derivation of each rule is depicted by the reduced attributes with a layered manner. Therefore, the inconsistency is divided into two primary categories in terms of the reduced attributes. We introduce the notion of joint membership function wrt. the effectual joint attributes, and a classification method extended from the default decision generation framework is proposed to handle the inconsistency.