Research on Customer Churn Model with Least Square Support Vector Machine

China telecommunications market is becoming more competitive, the operators are facing the severe costumer churn problem, and how to predict and effectively reduce the costumer churn directly concerns the survival and development of every operator. Therefore, the least squares support vector machine...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 236-237; pp. 869 - 874
Main Author Xia, Tai Wu
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.11.2012
Subjects
Customer Churn Model
Least Squares Support Vector Machines (Ls-SVM)
Case Study
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Summary:China telecommunications market is becoming more competitive, the operators are facing the severe costumer churn problem, and how to predict and effectively reduce the costumer churn directly concerns the survival and development of every operator. Therefore, the least squares support vector machine(LS-SVM) algorithm is adopted to build customer churn model, mainly including data cleaning, normalization, building forecasting model, model prediction, etc. The case study shows that the customer churn prediction using the LS-LSV has high precision, small error and remarkable effect.
Bibliography:Selected, peer reviewed papers from the 2012 3rd International Conference on Information Technology for Manufacturing Systems (ITMS 2012), September 8-9, 2012, Qingdao, China
ISBN:3037855312
9783037855317
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.236-237.869