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智能适应组合模型用于多类不平衡的非静止数据流

Abdul Sattar Palli1,2, Jafreezal Jaafar3,4, Mohamad Hanif Md Saad5

  • 1Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, 32610, Seri Iskandar, Perak Darul Ridzuan, Malaysia. abdulsattarpalli@gmail.com.

Scientific reports
|July 2, 2025
PubMed
概括

本研究介绍了智能自适应组合模型 (SAEM),以解决多类数据流中的概念漂移和类不平衡. 通过适应数据变化和重新加权少数阶级,SAEM显著提高了在线机器学习模型的性能.

关键词:
概念适应 概念适应概念的漂移概念的漂移多类失衡是多类失衡.非静态数据流是非静态的数据流.在线机器学习在线机器学习

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