MSC-CSMC: A multi-objective semi-supervised clustering algorithm based on constraints selection and multi-source constraints for gene expression data

Many clustering techniques have been proposed to group genes based on gene expression data. Among these methods, semi-supervised clustering techniques aim to improve clustering performance by incorporating supervisory information in the form of pairwise constraints. However, noisy constraints inevit...

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Vydané v:	Frontiers in genetics Ročník 14; s. 1135260
Hlavní autori:	Wang, Zeyuan, Gu, Hong, Zhao, Minghui, Li, Dan, Wang, Jia
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 27.02.2023
Predmet:	constraint selection gene expression data Genetics multi-objective optimization multi-source constraints semi-supervised clustering gene expression data multi-objective optimization constraint selection multi-source constraints semi-supervised clustering
ISSN:	1664-8021, 1664-8021
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