A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model-Reference-Cited by-同舟云学术

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A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model

Published:2024-08-30 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

He Chenggang,Ding Chris H. Q.

Funder

Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology

NSFC Key Project of International (Regional) Cooperation and Exchanges

Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-71168-x.pdf

Reference44 articles.

1. Fujo, S. W. et al. Customer churn prediction in telecommunication industry using deep learning. Inf. Sci. Lett. 11(1), 24 (2022).

2. Xie, Y., Li, X., Ngai, E. & Ying, W. Customer churn prediction using improved balanced random forests. Expert Syst. Appl. 36(3), 5445–5449 (2009).

3. De Caigny, A., Coussement, K. & De Bock, K. W. A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees. Eur. J. Oper. Res. 269(2), 760–772 (2018).

4. Ahmad, A. K., Jafar, A. & Aljoumaa, K. Customer churn prediction in telecom using machine learning in big data platform. J. Big Data 6(1), 1–24 (2019).

5. He, C., Ding, C.H., Chen, S., Luo, B. Intelligent machine learning system for predicting customer churn. In: 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), pp. 522–527 (2021). IEEE.

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