DOI: 10.7763/IJCTE.2012.V4.492
Class Labeling of Bank Credit’s Customers Using AHP and SAW for Credit Scoring with Data Mining Algorithms
Abstract—One of the most important parts in credit scoring is determining the class of customers to run the Data Mining Classification algorithms. The purpose of this research is allocating the Labels of Credit customers with using of AHP and SAW methods. Here, in the first step, each customer is labeled by AHP and SAW and then the data mining algorithms are run. In this way, via this method the acquired results of data mining algorithms can be improved. The presented steps have been studied in an Iranian Bank as empirical study.
Index Terms—Data mining, credit scoring, classification, labeling, SAW, AHP.
The authors are with the Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran (e-mail: Nadali.ahmad@gmail.com, Pourdarab.sanaz@yahoo.com, Hamideslami.na@gmail.com).
Cite: Ahmad Nadali, Sanaz Pourdarab, and Hamid Eslami Nosratabadi, "Class Labeling of Bank Credit’s Customers Using AHP and SAW for Credit Scoring with Data Mining Algorithms," International Journal of Computer Theory and Engineering vol. 4, no. 3, pp. 401-404, 2012.