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language
eng
Author
Tamatani, Mitsuru
Description
This paper is based on the author's thesis, “Pattern recognition based on naive canonical correlations in high dimension low sample size”. This paper is concerned with discriminant analysis for multi-class problems in a High Dimension Low Sample Size (hdlss) context. The proposed discrimination method is based on canonical correlations between the predictors and response vector of class label. We investigate the asymptotic behavior of the discrimination method, and evaluate bounds for its misclassication rate.
Subject
high dimension low sample size
canonical correlations
consistency
misclassification
multi-class linear discriminant analysis
Journal Title
島根大学総合理工学研究科紀要. シリーズB
Volume
48
Start Page
15
End Page
26
ISSN
13427121
Published Date
2015-03
NCID
AA12638295
Publisher
島根大学総合理工学研究科
NII Type
Departmental Bulletin Paper
Format
PDF
Text Version
出版社版
OAI-PMH Set
Interdisciplinary Graduate School of Science and Engineering
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