Enhancing customer retention with machine learning: A comparative analysis of ensemble models for accurate churn prediction
This paper investigates the use of machine learning models for customer churn prediction, focusing on the comparative effectiveness of ensemble approaches such as XGBoost and Random Forest with classical classifiers. The study evaluates the benefits and shortcomings of each strategy in dealing with...
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| Main Authors: | Payam Boozary, Sogand Sheykhan, Hamed GhorbanTanhaei, Cosimo Magazzino |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | International Journal of Information Management Data Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096825000138 |
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