Title :
The study on feature selection in customer churn prediction modeling
Author :
Wu, Yin ; Qi, Jiayin ; Wang, Chen
Author_Institution :
Sch. of Economic & Manage., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
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.
Keywords :
customer relationship management; learning (artificial intelligence); customer churn prediction modeling; feature selection; Conference management; Economic forecasting; Feature extraction; Filters; Machine learning; Machine learning algorithms; Pattern recognition; Predictive models; Statistics; Text categorization; Algorithm Experiment; Customer Churn Prediction; Feature Selection; Framework Design;
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2009.5346171
