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Updated: Jul 9, 2025

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
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一种基于高斯混合模型的新蒙特卡洛采样方法,用于不平衡数据分类

Gang Chen1, Binjie Hou1, Tiangang Lei1

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

Mathematical biosciences and engineering : MBE
|December 5, 2023
PubMed
概括

基于高斯混合模型 (MCS-GMM) 的新蒙特卡洛采样算法通过生成现实的合成样本,有效地解决了不平衡的数据分类问题. 这种方法通过考虑数据的复杂性和减少重叠来提高模型性能,优于现有技术.

关键词:
高斯混合物模型模型蒙特卡洛采样 蒙特卡洛采样不平衡的数据不平衡的数据.这是一种过量采样技术.概率密度函数是一个概率密度函数.

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