多粒度模糊自动编码器用于高维数据中的歧视性特征选择

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Updated: Sep 19, 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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Yuepeng Chen, Weiping Ding, Jiashuang Huang

    IEEE transactions on neural networks and learning systems
    |June 2, 2025
    PubMed
    概括

    本研究引入了一种使用多粒度模糊自编码器 (FAE) 的新型特征选择方法,以改进生物数据分析. FAE方法有效地处理噪音数据,提高复杂数据集的分类准确性和稳定性.

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