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

Title
Using visual statistical inference to better understand random class separations in high dimension, low sample size data
Authors
Roy Chowdhury N.Cook D.Hofmann H.Majumder M.Lee E.-K.Toth A.L.
Ewha Authors
이은경
SCOPUS Author ID
이은경scopusscopus
Issue Date
2014
Journal Title
Computational Statistics
ISSN
0943-4062JCR Link
Citation
Computational Statistics
Publisher
Springer Verlag
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article in Press
Abstract
Data mining; Lineup; Projection pursuit; Statistical graphics; Visualization
DOI
10.1007/s00180-014-0534-x
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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