Abstract

Credit assessment is a very typical classification problem in Data Mining. A type of classification technique that has attracted an increasing number of attempts in recent years is finding classification rules based on association rule mining techniques. This paper aims to contribute to this kind of research by classifying the bank's customers via association rules with the use of the APRIORI algorithm and CRISP-DM methodology and considering the Experts' opinions to filter the obtained rules and define the Membership functions for the considered criteria, finally a Fuzzy Expert System is designed based on the selected rules from association rules to specify the Credit Degree of banks' customers. The presented steps have been studied in an Iranian Bank as empirical study.