DocumentCode
2569211
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
fYear
2009
fDate
11-14 Oct. 2009
Firstpage
3205
Lastpage
3210
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location
San Antonio, TX
ISSN
1062-922X
Print_ISBN
978-1-4244-2793-2
Electronic_ISBN
1062-922X
Type
conf
DOI
10.1109/ICSMC.2009.5346171
Filename
5346171
Link To Document