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Updated: Jan 31, 2026

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
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适应性模糊集群引导的简单,快速和高效的特征选择,用于高维和高度不平衡的二进制类生物信息学微阵列数据

Yi Wei Tye1, XinYing Chew2, Umi Kalsom Yusof3

  • 1School of Computer Sciences, Universiti Sains Malaysia, Gelugor, Penang, 11800, Malaysia.

Scientific reports
|January 29, 2026
PubMed
概括

本研究介绍了自适应模糊集群引导的简单,快速和高效 (AFCG-SFE) 模型,用于在不平衡的微阵列数据中进行特征选择. AFCG-SFE有效地识别了歧视性特征,大大提高了分类性能并减少了数据的复杂性.

关键词:
二元不平衡分类是二元不平衡的分类.复杂性指标是指复杂性的指标.进化特征选择是进化特征的选择.模糊的聚类模糊的聚类.高维数据是高维数据.微阵列数据的数据

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