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Three Categories Customer Churn Prediction Based on the Adjusted Real Adaboost

机译:基于调整后的真实Adaboost的三类客户流失预测

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摘要

It is necessary for enterprises to establish a customer churn management system. In this article, we take the heterogeneity into consideration and divide the churn people into two classes according to the data characteristics. Moreover, we try to modify the bias of multi-class unbalanced data classification. Then we propose a new method based on Real Adaboost for the problem. The proposed method takes the within-group error into consideration and creates another view of reweighing the cases. Empirical study on our sample data shows that the new method performs better than the other method.
机译:企业必须建立客户流失管理系统。在本文中,我们考虑了异构性,并根据数据特征将流失人员分为两类。此外,我们尝试修改多类不平衡数据分类的偏差。然后针对该问题提出了一种基于Real Adaboost的新方法。所提出的方法考虑了组内误差,并创建了重新称量案例的另一种观点。对样本数据的实证研究表明,新方法的性能优于其他方法。

著录项

  • 来源
  • 作者

    Miao Liu;

  • 作者单位

    State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China;

    Statistics School, Renmin University of China, Beijing, China;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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