Gene expression selection for cancer classification using intelligent collaborative filtering and hamming distance guided multi-objective swarm optimization

High dimensional microarray cancer datasets contain thousands of genes with a very few numbers of samples. High class imbalance, presence of noisy and redundant genes and overlapping nature of extracted features among different disease classes deteriorate the disease prediction accuracy. An intellig...

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Bibliographic Details

Published in:	Applied soft computing Vol. 170; p. 112654
Main Authors:	Agarwalla, Prativa, Mukhopadhyay, Sumitra
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.02.2025
Subjects:	Classification DNA microarray Feature selection Multi-objective algorithm Particle swarm optimization (PSO) DNA microarray Feature selection Multi-objective algorithm Particle swarm optimization (PSO) Classification
ISSN:	1568-4946
Online Access:	Get full text
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