Research on Customer Churn Model with Least Square Support Vector Machine

Tai Wu Xia

doi:10.4028/www.scientific.net/AMM.236-237.869

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 236-237Research on Customer Churn Model with Least Square...

Research on Customer Churn Model with Least Square Support Vector Machine

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 236-237)

Pages:

869-874

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.236-237.869

Citation:

Cite this paper

Online since:

November 2012

Authors:

Tai Wu Xia

Keywords:

Case Study, Customer Churn Model, Least Squares Support Vector Machines (Ls-SVM)

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