Author(s)

Hui Wu¹, Chang-Chun Wang²

¹Department of Mathematics, Clark Atlanta University, Atlanta, GA, USA.
²International Monetary Fund, Washington DC, USA.

In this paper we applied the technique of Self Organizing Map (SOM) to segment individuals based on their credit information. SOM is an unsupervised machine learning method that reduces data complexity and dimensionality while keeping sits original topology, which is superior to other dimension reduction methods especially when features in data have unclear nonlinear relations. Through this method we provide more clear and intuitive segmentation that other traditional methods cannot achieve.

Self Organizing Map, Clustering, Machine Learning, Credit Default

Wu, H. and Wang, C. (2018) Customer Segmentation of Credit Card Default by Self Organizing Map. American Journal of Computational Mathematics, 8, 197-202. doi: 10.4236/ajcm.2018.83015.