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Author Iwamura, Masakazu ♦ Aso, Hirotomo
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Recognition Accuracy Reduction ♦ Recognition Performance Reduction ♦ Training Sample ♦ Statistical Pattern Recognition ♦ Experimental Result ♦ Estimation Error ♦ Bad Influence ♦ Various Method ♦ New Method ♦ Recognition Accuracy
Description In statistical pattern recognition, parameters of distributions are usually estimated from training samples. It is well known that shortage of training samples causes estimation errors which reduce recognition accuracy. By studying estimation errors of eigenvalues, various methods of avoiding recognition accuracy reduction have been proposed. However, estimation errors of eigenvectors have not been considered enough. In this paper, we investigate estimation errors of eigenvectors to show these errors are another factor of recognition performance reduction. We propose a new method for modifying eigenvalues in order to reduce bad influence caused by estimation errors of eigenvectors. Effectiveness of the method is shown by experimental results. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2000-01-01
Publisher Institution In: Proc. ICPR. Volume 2