文章基本信息

标题：A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry
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作者：Nilam Nur Amir Sjarif ; Muhammad Rusydi Mohd Yusof ; Doris Hooi-Ten Wong 等
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2019
卷号：11
期号：2
页码：46-59
出版社：International Center for Scientific Research and Studies
摘要：Customer churn in telecommunication industry is actually a serious issue. The Telco company needs to have a churn prediction model to prevent their customer from moving to another telco. Therefore, the objective of this paper is to propose the customer churn prediction using Pearson Correlation and K Nearest Neighbor algorithm. The algorithm is validated via training and testing dataset with the ratio 70:30. Based on experiment, the result shows that the K Nearest Neighbor algorithm performs well compared to the others with the accuracy for training is 80.45% and testing 97.78%.
关键词：Customer Churn Prediction; Pearson Correlation; Machine Learning; K Nearest Neighbor.