Prediction of Customer Behavior Changing via a Hybrid Approach
Author:
Affiliation:
1. Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan
2. Group Retail Planning Center, Far Eastern, New Taipei, Taiwan
3. Purdue University, West Lafayette, IN, USA
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/8782664/10375894/10334013.pdf?arnumber=10334013
Reference41 articles.
1. Improving prediction of customer behavior in nonstationary environments;Yan,2001
2. A Big Data Clustering Algorithm for Mitigating the Risk of Customer Churn
3. A comparison of machine learning techniques for customer churn prediction
4. An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes
5. Just-in-time customer churn prediction in the telecommunication sector
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