Linked Life Data

10329293

Source:http://linkedlifedata.com/resource/pubmed/id/10329293

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1999-7-7
pubmed:abstractText
Generalization can be defined quantitatively and can be used to assess the performance of principal component analysis (PCA). The generalizability of PCA depends on the number of principal components retained in the analysis. We provide analytic and test set estimates of generalization. We show how the generalization error can be used to select the number of principal components in two analyses of functional magnetic resonance imaging activation sets.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1053-8119
pubmed:author
pubmed:copyrightInfo
Copyright 1999 Academic Press.
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
534-44
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Generalizable patterns in neuroimaging: how many principal components?
pubmed:affiliation
Department of Mathematical Modeling, Technical University of Denmark, Building 321, Lyngby, DK-2800, Denmark. lkhansen@imm.dtu.dk
pubmed:publicationType
Journal Article, Clinical Trial, Research Support, U.S. Gov't, P.H.S., Randomized Controlled Trial, Research Support, Non-U.S. Gov't