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Comparison of Methods for Handling Imbalanced Data in Customer Churn Prediction with Feature Selection Using SHAP and mRMR Frameworks Cover

Comparison of Methods for Handling Imbalanced Data in Customer Churn Prediction with Feature Selection Using SHAP and mRMR Frameworks

Cybernetics and Information Technologies
Volume 25 (2025): Issue 3 (September 2025)
By: Luong Thanh Tam,  Luong Gia Vi and  Nguyen Manh Tuan  
Open Access
|Sep 2025

Authors

Luong Thanh Tam

tamluong.31231024238@st.ueh.edu.vn

Faculty of Business Information and Technology, University of Economic Ho Chi Minh City, Vietnam

Luong Gia Vi

viluong.31231024175@st.ueh.edu.vn

Faculty of Business Information and Technology, University of Economic Ho Chi Minh City, Vietnam

Nguyen Manh Tuan

tuannm@ueh.edu.vn

Faculty of Business Information and Technology, University of Economic Ho Chi Minh City, Vietnam
DOI: https://doi.org/10.2478/cait-2025-0023 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
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Language: English
Page range: 68 - 87
Published on: Sep 25, 2025
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Machine learning,
Customer churn,
Imbalanced data,
Resampling,
Explainable AI
Related subjects:
Computer sciences,
Information technology

© 2025 Luong Thanh Tam, Luong Gia Vi, Nguyen Manh Tuan, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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