A Note on Quality Measures for Fuzzy Association Rules

Abstract

Several approaches generalizing association rules to fuzzy association rules have been proposed so far. While the formal specification of fuzzy associations is more or less straightforward, the evaluation of such rules by means of appropriate quality measures assumes an understanding of the semantic meaning of a fuzzy rule. In this respect, most existing proposals can be considered ad-hoc to some extent. In this paper, we suggest a theoretical basis of fuzzy association rules by generalizing the classification of the data stored in a database into positive, negative, and irrelevant examples of a rule