Presentation 1998/7/24
On the Orthonormal Discriminant Vector Method in Small Training Sample Size Situations
Takanobu Miyamoto, Yoshihiko Hamamoto,
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Abstract(in English) In the small-sample, high-dimensional setting, the estimation error of a covariance matrix causes practical difficulties in designing a feature extractor based on the Fisher criterion. In this paper, we try to reduce the estimation error by using the Toeplitz method or regularization method. Experimental results support our approach.
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Keyword(in English) Feature extraction / orthonormal discriminant vector method / within-class scatter matrix / Toeplitz method / regularization
Paper # IE98-39,PRMU98-62,MVE98-62
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Conference Information
Committee MVE
Conference Date 1998/7/24(1days)
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Registration To Media Experience and Virtual Environment (MVE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) On the Orthonormal Discriminant Vector Method in Small Training Sample Size Situations
Sub Title (in English)
Keyword(1) Feature extraction
Keyword(2) orthonormal discriminant vector method
Keyword(3) within-class scatter matrix
Keyword(4) Toeplitz method
Keyword(5) regularization
1st Author's Name Takanobu Miyamoto
1st Author's Affiliation Faculty of Engineering, Yamaguchi University()
2nd Author's Name Yoshihiko Hamamoto
2nd Author's Affiliation Faculty of Engineering, Yamaguchi University
Date 1998/7/24
Paper # IE98-39,PRMU98-62,MVE98-62
Volume (vol) vol.98
Number (no) 208
Page pp.pp.-
#Pages 8
Date of Issue