Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning
Background Imbalanced and overlapped data in customer churn prediction significantly impact classification results. Various sampling and hybrid sampling methods have demonstrated effectiveness in addressing these issues. However, these methods have not performed well with classical machine learning...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2025-06-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-2949.pdf |
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