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An Algorithm for Predicting Customer Churn via BP Neural Network Based on Rough Set

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4 Author(s)
Xu, E. ; Dept. of Comput. Sci., Liaoning Inst. of Technol., Jinzhou ; Shao Liangshan ; Gao Xuedong ; Zhai Baofeng

To solve the prediction of customer churn, the paper proposed a new algorithm. Based on rough set theory, the algorithm used the consistency of condition attributes and decision attributes in information table, and the conception of super-cube and scan vector to discretize the continuous attributes, reduce the redundant attributes. And furthermore, it took BP neural network as the calculating tool to predict customer churn. The experimental results showed the refined data by rough set was more concise and more convenient to be applied in BP neural network, whose prediction result was more accurate. So, the algorithm via BP neural network based on rough set theory is efficient and effective

Published in:

Services Computing, 2006. APSCC '06. IEEE Asia-Pacific Conference on

Date of Conference:

12-15 Dec. 2006