The week's pick
Reseach Article
Customer Segmentation of Bank based on Data Mining ñ Security Value based Heuristic Approach as a Replacement to K-means Segmentation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 19 - Number 8 |
| Year of Publication: 2011 |
| Authors: Shashidhar HV, Subramanian Varadarajan |
10.5120/2383-3145
|
Shashidhar HV, Subramanian Varadarajan . Customer Segmentation of Bank based on Data Mining ñ Security Value based Heuristic Approach as a Replacement to K-means Segmentation. International Journal of Computer Applications. 19, 8 ( April 2011), 13-18. DOI=10.5120/2383-3145
Abstract
K-means segmentation algorithm can be applied to Customer Segmentation in Banks. If loan over-due amount of bank customers are normally distributed, then K-means can be used. In cases of significant outliers, K-means segmentation algorithm cannot be applied. In our proposed solution, bank loan customers are segmented based on security value and loan over-due amount. Proposed solution addresses segmentation issues on outliers and provides security value based heuristic approach as a replacement to K-means segmentation.
References
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