Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates
type: Item
instance of: scholarly article
title: Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates
zbMATH Open document ID: 1402.92227
author: Ashish Anand
author: P. N. Suganthan
published in: Journal of Theoretical Biology
publication date: 2018-11-16T00:00:00Z
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 92D10
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6980158
zbMATH Keywords: class-wise selected genes
zbMATH Keywords: multiclass SVM
zbMATH Keywords: probability outputs SVM
zbMATH Keywords: cancer subtype classification
zbMATH Keywords: ensemble SVM
describes a project that uses: R
describes a project that uses: Memtype-2L
describes a project that uses: Signal-3L
describes a project that uses: Signal-CF
describes a project that uses: EzyPred
describes a project that uses: Euk-mPLoc
describes a project that uses: HIVcleave
describes a project that uses: Hum-PLoc
describes a project that uses: LIBSVM
describes a project that uses: ProtIdent
describes a project that uses: Euk-PLoc
describes a project that uses: Cell-PLoc
MaRDI profile type: Publication
full work available at URL: j.jtbi.2009.04.013
OpenAlex ID: W2023984830
Wikidata QID: Q83752607
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cites work: Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes
DOI: 10.1016/J.JTBI.2009.04.013
description: scientific article; zbMATH DE number 6980158