The Study on Feature Selection in Customer Churn Prediction Modeling

被引：3
|
作者：
Wu, Yin [1 ]
Qi, Jiayin [1 ,2 ]
Wang, Chen [3 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing 100088, Peoples R China
[2] Univ Washington Business Sch, Dept Informat Syst & Operat Management, Seattle, WA 98195 USA
[3] IBM Corp, IBM China Res Lab, Beijing, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9 | 2009年
基金：
中国国家自然科学基金;
关键词：
Customer Churn Prediction; Feature Selection; Framework Design; Algorithm Experiment; FLOATING SEARCH METHODS; FEATURE SPACE THEORY;
D O I：
10.1109/ICSMC.2009.5346171
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
When the customer churn prediction model is built, a large number of features bring heavy burdens to the model and even decrease the accuracy. This paper is aimed to review the feature selection, to compare the algorithms from different fields and to design a framework of feature selection for customer churn prediction. Based on the framework, the author experiment on the structured module with some telecom operator's marketing data to verify the efficiency of the feature selection framework.
引用
收藏
页码：3205 / +
页数：2
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