文章基本信息

标题：Initializing Genetic Programming using Fuzzy Clustering and its Application in Churn Prediction in the Telecom Industry
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作者：Bashar AlShboul ; Hossam Faris ; Nazeeh Ghatasheh 等
期刊名称：Malaysian Journal of Computer Science
印刷版ISSN：0127-9084
出版年度：2015
卷号：28
期号：3
出版社：University of Malaya * Faculty of Computer Science and Information Technology
摘要：Customer defection or "churn" rate is critically important since it leads to serious business loss. Therefore, many telecommunication companies and operators have increased their concern about churn management and investigated statistical and data mining based approaches which can help in identifying customer churn. In this paper, a churn prediction framework is proposed aiming at enhancing the predictability of churning customers. The framework is based on combining two heuristic approaches; Fast Fuzzy CMeans (FFCM) and Genetic Programming (GP). Considering the fact that GP suffers three different major problems: sensitivity towards outliers, variable results on various runs, and resource expensive training process, FFCM was first used to cluster the data set and exclude outliers, representing abnormal customers’ behaviors, to reduce the GP possible sensitivity towards outliers and training resources. After that, GP is applied to develop a classification tree. For the purpose of this work, a data set was provided by a major Jordanian telecommunication mobile operator.
关键词：Churn Prediction; Fuzzy Clustering; Genetic Programming