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通过基于两阶段学习的集体学习改善不平衡分类

Na Liu1, Jiaqi Wang1, Yongtong Zhu1

  • 1Institute of Machine Intelligence, University of Shanghai for Science and Technology, Shanghai, China.

Frontiers in computational neuroscience
|January 22, 2024
PubMed
概括

本研究引入了一种新的两阶段学习方法,以解决图像分类的深度学习中的数据不平衡. 该方法通过重新权重样本并使用合并方法来减轻分布变化,从而改善不平衡数据集的模型性能.

关键词:
一个共变的轮班.这种不平衡是不平衡的.罗吉特的调整调整.在之前的轮班之前.重新加重重权重,重新加重权重

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