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优化客户流失预测使用基于表式生成对抗网络 (GAN) 的混合采样方法和成本敏感的学习

I Nyoman Mahayasa Adiputra1, Paweena Wanchai1, Pei-Chun Lin2

  • 1College of Computing, Khon Kaen University, Khon Kaen, Thailand.

PeerJ. Computer science
|June 26, 2025
PubMed
概括

CostLearnGAN是一种新的混合采样方法,通过处理不平衡的数据,增强了用于预测客户流失的经典机器学习. 这种方法提高了模型的性能和稳定性,为大型数据集提供了高效的解决方案.

关键词:
具有成本敏感性的学习.客户流失预测的预测基于GAN的混合采样方法.

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