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language |
eng
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Author |
Tamatani, Mitsuru
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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.
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Subject | high dimension low sample size
canonical correlations
consistency
misclassification
multi-class linear discriminant analysis
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Journal Title |
島根大学総合理工学研究科紀要. シリーズB
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Volume | 48
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Start Page | 15
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End Page | 26
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ISSN | 13427121
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Published Date | 2015-03
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NCID | AA12638295
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Publisher | 島根大学総合理工学研究科
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NII Type |
Departmental Bulletin Paper
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Format |
PDF
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Text Version |
出版社版
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OAI-PMH Set |
Interdisciplinary Graduate School of Science and Engineering
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他の一覧 |