Validation Method of Fuzzy Association Rules Based on Fuzzy Formal Concept Analysis and StructuralEquation Model

摘要

In order to treat and analyze real datasets, fuzzy association rules have been proposed. Severalalgorithms have been introduced to extract these rules. However, these algorithms suffer fromthe problems of utility, redundancy and large number of extracted fuzzy association rules. Theexpert will then be confronted with this huge amount of fuzzy association rules. The task ofvalidation becomes fastidious. In order to solve these problems, we propose a new validationmethod. Our method is based on three steps. (i) We extract a generic base of non redundantfuzzy association rules by applying EFAR-PN algorithm based on fuzzy formal concept analysis.(ii) we categorize extracted rules into groups and (iii) we evaluate the relevance of these rulesusing structural equation model.