Improving Classification of Cancer and Mining Biomarkers from Gene Expression Profiles Using Hybrid Optimization Algorithms and Fuzzy Support Vector Machine

Background: Gene expression data are characteristically high dimensional with a small sample size in contrast to the feature size and variability inherent in biological processes that contribute to difficulties in analysis. Selection of highly discriminative features decreases the computational cost...

詳細記述

書誌詳細

出版年:	Journal of Medical Signals and Sensors
主要な著者:	Niloofar Yousefi Moteghaed, Keivan Maghooli, Masoud Garshasbi
フォーマット:	論文
言語:	英語
出版事項:	Wolters Kluwer Medknow Publications 2018-01-01
主題:	Cancer classification fuzzy support vector machine gene expression genetic algorithm particle swarm optimization algorithm
オンライン･アクセス:	http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2018;volume=8;issue=1;spage=1;epage=11;aulast=Moteghaed