Abstract—ONE of the most important parts in credit scoring is determining the class of customers to run the Data Mining algorithms. The purpose of this research is estimating the Label of Credit customers via Fuzzy Expert System. Here the class of customers has been specified by a Fuzzy Expert System and then the Data Mining Algorithms have been run on the final data with Clementine software. The presented steps have been studied in an Iranian Bank as empirical study.
Index Terms—Data Mining, Fuzzy Expert System, Credit Scoring, Labeling, Clementine.
First Author, Hamid Eslami Nosratabadi is with the Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran (Corresponding author’s email is Hamideslami.na@gmail.com).
Second Author, Sanaz Pourdarab is with the Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran (Email:Pourdarab.sanaz@yahoo.com).
Third Author, Ahmad Nadali is with the Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran (Email:Nadali.ahmad@gmail.com).
Cite: Hamid Eslami Nosratabadi, Sanaz Pourdarab and Ahmad Nadali, "A New Approach for Labeling the Class of Bank Credit Customers via Classification Method in Data Mining," International Journal of Information and Education Technology vol. 1, no. 2, pp. 150-155, 2011.