Construction of Bayesian Classifiers with GA for Predicting Customer Retention

Author

Shao, Hongmei ; Zheng, Gaofeng ; An, Fengxian

Author_Institution

Coll. of Math. & Comput. Sci., China Univ. of Pet., Dongying

Volume

1

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

181

Lastpage

185

Abstract

In this paper, a novel Bayesian classifier model is constructed based on genetic algorithms (GA) for the prediction of customer churn. Experiment results have shown that it not only matches potential churning customers well from the large amount of validation data but also shows higher classifying precision compared with the other three Bayesian classifier models. Recently, the model has been adopted by a Japanese enterprise to successfully handle some business problems of potential churning customers prediction.

Keywords

Bayes methods; customer relationship management; genetic algorithms; pattern classification; Bayesian classifier model; CRM; Japanese enterprise business; customer churn prediction; customer retention prediction; genetic algorithm; Bayesian methods; Credit cards; Customer relationship management; Data mining; Genetic algorithms; Niobium; Petroleum; Potential well; Predictive models; Profitability; Bayesian classifiers; Construction; Customer retention; Genetic algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2008. ICNC '08. Fourth International Conference on

Conference_Location

Jinan

Print_ISBN

978-0-7695-3304-9

Type

conf

DOI

10.1109/ICNC.2008.724

Filename

4666835