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Updated: Jan 10, 2026

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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一个新的精英引导的混合元启发算法,用于高效的特征选择

Zichuan Chen1, Bin Fu2, Yangjian Yang2

  • 1Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia.

Biomimetics (Basel, Switzerland)
|November 26, 2025
PubMed
概括

本研究介绍了一种精英引导的混合北方鱼优化 (EH-NGO) 算法,用于有效的特征选择. 通过有效地识别最佳特征子集,EH-NGO提高了机器学习模型的准确性,优于现有方法.

关键词:
北方戈斯霍克的优化勘探 - 开采 - 开发功能选择 功能选择的元启发式算法.垂直交叉突变是垂直交叉突变.

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