广东工业大学学报Issue(3)：67-72,6.DOI:10.3969/j.issn.1007-7162.2015.03.013
改进的贝叶斯分类方法在电信客户流失中的研究与应用
Research and Application of Improved Bayes Algorithm for the Telecommunication Customer Churn
摘要
Abstract
With the increasing competition of telecom market, customer churn became one of the focused problems.Because the telecommunication data is huge and has the characteristic of time series, this pa-per proposes an improved Bayesian classification to study the customer churn problem.The improved Bayesian classification model is designed to make up for the shortcomings of the former Bayes which as-sumed that each attribute has the same effect on the classification results.Furthermore, by coping with the increasing data, this paper explores the incremental learning method to improve the accuracy of the classifier.The experimental results show that the proposed method has higher accuracy.关键词
贝叶斯分类/电信数据/增量学习/客户流失/预测Key words
Bayesian classification/telecommunication data/incremental learning method/customer churn/prediction分类
信息技术与安全科学引用本文复制引用
杨婷,滕少华..改进的贝叶斯分类方法在电信客户流失中的研究与应用[J].广东工业大学学报,2015,(3):67-72,6.基金项目
教育部重点实验室基金资助项目（110411）；广东省自然科学基金资助项目（10451009001004804，9151009001000007）；广东省科技计划项目（2012B091000173，2013B090200017，2013B010401029，2013B010401034）；广州市科技计划项目 （）
