Presentation 1996/5/17
A proposal for parameter of Regularized Discriminant Analysis on Statistical Pattern Classifier
Tetsuo TAKESHITA, Shigeyuki NOZAWA, Jun-ichiro TORIWAKI,
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Abstract(in English) When we design a statistical pattern classifier, it is well known that classification performance remarkably decreases in the case of limited sample size, because of estimation errors of covariance matrices. Friedman proposed Regularized Discriminant Analysis(RDA) to deal with this problem as one of the method of designing classifier. RDA needs two parameters, but no practical method on how to decide the value of these parameter has been proposed. Authors found a simple equation to decide one parameter of RDA and confirmed its effectiveness making use of Monte Carlo simulation. They also applied this practical method to the character recognition experiments and got good results.
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Keyword(in English) pattern classifier / quadratic discriminant function / covariance matrix / character recognition / ridge regression
Paper # PRMU96-13
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Conference Information
Committee PRMU
Conference Date 1996/5/17(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A proposal for parameter of Regularized Discriminant Analysis on Statistical Pattern Classifier
Sub Title (in English)
Keyword(1) pattern classifier
Keyword(2) quadratic discriminant function
Keyword(3) covariance matrix
Keyword(4) character recognition
Keyword(5) ridge regression
1st Author's Name Tetsuo TAKESHITA
1st Author's Affiliation Toyota National College of Technology Dept. of Information and Computer Eng.()
2nd Author's Name Shigeyuki NOZAWA
2nd Author's Affiliation Toyota National College of Technology Dept. of Information and Computer Eng.
3rd Author's Name Jun-ichiro TORIWAKI
3rd Author's Affiliation Nagoya University Faculty of Engineering
Date 1996/5/17
Paper # PRMU96-13
Volume (vol) vol.96
Number (no) 41
Page pp.pp.-
#Pages 8
Date of Issue