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

被引：4
|
作者：
Sniegula, Anna [1 ]
Poniszewska-Maranda, Aneta [2 ]
Popovic, Milan [1 ]
机构：
[1] Univ Lodz, Dept Informat Econ, Lodz, Poland
[2] Lodz Univ Technol, Inst Informat Technol, Lodz, Poland
来源：
IIWAS2019: THE 21ST INTERNATIONAL CONFERENCE ON INFORMATION INTEGRATION AND WEB-BASED APPLICATIONS & SERVICES | 2019年
关键词：
machine learning; predictive analytics; neural networks; decision trees; k-means clustering; client churn prediction;
D O I：
10.1145/3366030.3366109
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：640 / 644
页数：5
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