Uniformly subsampled ensemble (USE) for churn management: Theory and implementation

Authors:
Namhyoung Kim;Kyu-Hwan Jung;Yong Seog Kim;Jaewook Lee
Affiliations:
Department of Industrial and Management Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja, Pohang 790-784, South Korea;SK Telecom, 11, Euljiro 2-ga, Jung-gu, Seoul 100-999, South Korea;Department of Management Information Systems, Utah State University, Logan, UT 84322, USA;Department of Industrial Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-744, South Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

The present paper explores the possible application of a new ensemble model. The model, which is based on multiple SVM classifiers, is employed to address churner identification problems in the mobile telecommunication industry, a sector in which the role of customer retention program becomes increasingly important due to its very competitive business environment. In particular, the current study introduces a uniformly subsampled ensemble (USE) model of SVM classifiers, not only to reduce the computational complexity of large-scale data, but also to boost the reliability and accuracy of calibrated models on data sets with highly skewed class distributions. According to our experiments, the performance of the USE SVM model is superior compared to all single and ensemble models. It is more scalable than well-known ensemble models as well.