Study of machine learning methods for customer churn prediction in telecommunication company

Anna Śniegula, A. Poniszewska-Marańda, M. Popović
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引用次数: 5

Abstract

The paper presents the results of investigation which machine learning techniques are most suited for customer churn prediction. Different approaches were compared, starting from the simple K-means method, through decision trees, ending with the artificial neural network. The authors trained the models with each method and predicted whether a customer is going to leave the current telecommunication company.
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电信企业客户流失预测的机器学习方法研究
本文介绍了哪种机器学习技术最适合客户流失预测的调查结果。比较了不同的方法,从简单的K-means方法开始,经过决策树,最后以人工神经网络结束。作者用每种方法训练模型,并预测客户是否会离开当前的电信公司。
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