Multiple Criteria Quadratic Programming for Fund Customer Churn Analysis

摘要：

Customer churn analysis and prediction play an important role in customer relationship management and improve benefit of enterprises. In recent years, classification models based on mathematical programming have been widely applied to customer churn analysis and have been proven to be powerful tools. In this paper, a new Multiple Criteria Quadratic Programming (MCQP) model is proposed and tested using fund customer dataset We use ten-fold cross validation to test the accuracy and stability of the model. Finally, we compare our model with other three well-known models: Decision Tree, Artificial Neural Networks and SVM. The results show that MCQP is accurate and stable for predicting the customer churn. Consequently, we can safely say that MCQP model is capable of providing stable and credible results in predicting customer churn.

关键词： Customer Chum MCQP Data Mining Artificial Neural Networks SVM

作者: Rui Wang GuangLi Nie

作者单位: Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, China Management School of Graduate University of Chinese Academy of Sciences, Beijing, China

会议类型: 国际会议

会议名称: The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

会议地点: 昆明、丽江

会议语种:英文

页码: 314-317

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）