DSpace at EWHA: Using visual statistical inference to better understand random class separations in high dimension, low sample size data

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DC Field	Value	Language
dc.contributor.author	이은경	*
dc.date.accessioned	2016-08-29T12:08:39Z	-
dc.date.available	2016-08-29T12:08:39Z	-
dc.date.issued	2014	*
dc.identifier.issn	0943-4062	*
dc.identifier.other	OAK-14431	*
dc.identifier.uri	https://dspace.ewha.ac.kr/handle/2015.oak/230325	-
dc.description.abstract	Data mining; Lineup; Projection pursuit; Statistical graphics; Visualization	*
dc.language	English	*
dc.publisher	Springer Verlag	*
dc.title	Using visual statistical inference to better understand random class separations in high dimension, low sample size data	*
dc.type	Article in Press	*
dc.relation.index	SCIE	*
dc.relation.index	SCOPUS	*
dc.relation.journaltitle	Computational Statistics	*
dc.identifier.doi	10.1007/s00180-014-0534-x	*
dc.identifier.wosid	WOS:000357469200001	*
dc.identifier.scopusid	2-s2.0-84908409258	*
dc.author.google	Roy Chowdhury N.	*
dc.author.google	Cook D.	*
dc.author.google	Hofmann H.	*
dc.author.google	Majumder M.	*
dc.author.google	Lee E.-K.	*
dc.author.google	Toth A.L.	*
dc.contributor.scopusid	이은경(57188770360;57217075385)	*
dc.date.modifydate	20240123125059	*