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一种基于Bootstrap方法和Wasserstein生成对抗网络的新不平衡数据过量抽样方法.

Binjie Hou1, Gang Chen2

  • 1Department of Mathematics, Dalian Maritime University, Dalian 116026, China.

Mathematical biosciences and engineering : MBE
|March 29, 2024
PubMed
概括

这项研究引入了一种新的过量采样算法,Bootstrap方法-Wasserstein GAN (BM-WGAN),以解决生物数据中的类不平衡. BM-WGAN 增强了少数类数据生成,大大提高了对现有方法的分类性能.

关键词:
启动方式 (BM)数据生成数据的数据生成.不平衡的数据不平衡的数据.不平衡的数据,生成对抗网络 (GANs).一个概率分布的概率分布.

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