A Bagging Approach to Customer Churn Prediction

Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

ICISE02_095

تاریخ نمایه سازی: 25 آذر 1395

Abstract:

Customer churn prediction plays an important role in customer relationship management. To do so, classification algorithms are powerful tools to predict the churner customers in the real world. In this paper, the customer churn prediction is considered as a binary classification problem. The aim of this paper is to apply an ensemble approach based on bagging algorithm for customer churn prediction. It is demonstrated that a bagging approach for base classifiers can results better prediction performance. The proposed approaches are applied to a real dataset to illustrate the Bagging effectiveness. The results are compared with other base classifiers.

Authors

Sara Tavassoli

Department of industrial engineering Sadjad University of Technology Mashhad, Iran

Hamidreza Koosha

Department of industrial engineering Ferdowsi University of Mashhad Mashhad, Iran

Ebrahim Rezaee Nik

Department of industrial engineering Sadjad University of Technology Mashhad, Iran