通过聚合进化层次分类器来对抗多类不平衡的问题

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Updated: Jun 29, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
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Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

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Zhihan Ning, Zhixing Jiang, David Zhang

    IEEE transactions on neural networks and learning systems
    |April 8, 2024
    PubMed
    概括

    一种新的进化层次分类器森林 (FEHC) 方法有效地解决了多类失衡学习 (MCIL) 的挑战. 这种方法可以提高机器学习模型在分布不均的类分布的数据集上的性能.

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