Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization

The analysis of high-dimensional microarray gene expression data presents critical challenges, including excessive dimensionality, increased computational burden, and sensitivity to random initialization. Traditional optimization algorithms often produce inconsistent and suboptimal results, while fa...

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Bibliografische Detailangaben

Hauptverfasser:	Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	PeerJ Inc. 2025-05-01
Schriftenreihe:	PeerJ Computer Science
Schlagworte:	Microarray gene selection Multi-objective optimization Particle swarm optimization Neighborhood preservation
Online-Zugang:	https://peerj.com/articles/cs-2872.pdf
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