Title :
The Infromation Content of Fuzzy Relations and Fuzzy Rules
Author_Institution :
Beijing Normal Univ., Beijing
Abstract :
The appraisement of fuzzy relations is a significant problem in fuzzy theory. The related literatures done before almost focused on the similarity or equivalence fuzzy relations with a probability distribution preassigned. In this paper, a new measure named the information content of fuzzy relations is proposed, which estimates the information conveyed by a general fuzzy relations defined on multiple-domain without probability distribution preassigned. When fuzzy relation is taken as fuzzy set, the information content of fuzzy relation is compared with fuzzy entropy and specificity of fuzzy sets. Based on this new measure, a new concept, the information content of fuzzy rules, is defined, which focuses on the corresponding relation between input domain and output domain and can be used to appraise and choose fuzzy rules in rule mining.
Keywords :
fuzzy set theory; statistical distributions; fuzzy entropy; fuzzy relations; fuzzy rules; fuzzy set; information content; probability distribution; rule mining; Appraisal; Cybernetics; Educational institutions; Entropy; Fuzzy control; Fuzzy reasoning; Fuzzy sets; Machine learning; Measurement uncertainty; Probability distribution; Fuzzy entropy; Fuzzy relations; Fuzzy rules; Information content; Specificity;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370783