Sparse support vector machines with L
Classification
Feature selection
L(0) approximation
Metagenomics sequencing
SVM
Ultra-high dimensional data
Journal
Artificial intelligence in medicine
ISSN: 1873-2860
Titre abrégé: Artif Intell Med
Pays: Netherlands
ID NLM: 8915031
Informations de publication
Date de publication:
05 2019
05 2019
Historique:
received:
24
05
2018
revised:
31
03
2019
accepted:
27
04
2019
entrez:
6
6
2019
pubmed:
6
6
2019
medline:
28
4
2020
Statut:
ppublish
Résumé
Omics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L
Identifiants
pubmed: 31164207
pii: S0933-3657(18)30329-4
doi: 10.1016/j.artmed.2019.04.004
pmc: PMC6553498
mid: NIHMS1528945
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
134-141Subventions
Organisme : NCI NIH HHS
ID : P01 CA098912
Pays : United States
Organisme : NIDDK NIH HHS
ID : P01 DK046763
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001881
Pays : United States
Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.
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