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Linear Boundary Discriminant Analysis based on QR Decomposition

Linear Boundary Discriminant Analysis based on QR Decomposition
학술지명 Pattern Analysis and Applications ISSN 1433-7541
SCI 유무 SCI(E) 게재연월 2012-07 Vol. - No. -
표준화된 순위정보영향력지수 30.91 IF 0.739 Citation -

Linear Boundary Discriminant Analysis based on QR Decomposition
저자 JinHee Na, MyoungSoo Park, WooSung Kang, JinYoung Choi
초록
Linear boundary discriminant analysis (LBDA) shows good feature extraction performance in the classification problem. However, LBDA suffers from small sample size (SSS) problem and the computation time of it increases exponentially for datasets that are not sufficiently large compared with the number of features. To release these problems, we reformulate LBDA using QR decomposition, and this results in both reducing computation time and resolving SSS problem while classification performance is maintained.
keyword Linear boundary discriminant analysis, QR decomposition, computation time

Linear Boundary Discriminant Analysis based on QR Decomposition
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연구기관 한국과학기술연구원 연구책임자 박정민