期刊
INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE
卷 167, 期 -, 页码 101-112出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.procs.2020.03.187
关键词
Machine Learning; Logistic Regression; Logit Boost
Today in every industry weather, it is ISP, IT products, social network or mobile services there is the problem of customer churn (Customers changing their services from one service provider to another). However, in telecommunication the customers churning very frequently. As the market in telecom is fiercely competitive, in that case, companies proactively have to determine the customers churn by analyzing their behavior and try to put effort and money in retaining the customers. In this proposed model, two machine-learning techniques were used for predicting customer churn Logistic regression and Logit Boost. Experiment was carried out in the WEKA Machine-learning tool, along with a real database from an American company Orange. The result were shown in different evaluation measures. (C) 2020 The Authors. Published by Elsevier B.V.
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