Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.patcog.2009.10.004
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dc.titleA new and fast implementation for null space based linear discriminant analysis
dc.contributor.authorChu, D.
dc.contributor.authorThye, G.S.
dc.date.accessioned2014-12-12T07:29:26Z
dc.date.available2014-12-12T07:29:26Z
dc.date.issued2010-04
dc.identifier.citationChu, D., Thye, G.S. (2010-04). A new and fast implementation for null space based linear discriminant analysis. Pattern Recognition 43 (4) : 1373-1379. ScholarBank@NUS Repository. https://doi.org/10.1016/j.patcog.2009.10.004
dc.identifier.issn00313203
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/115561
dc.description.abstractIn this paper we present a new implementation for the null space based linear discriminant analysis. The main features of our implementation include: (i) the optimal transformation matrix is obtained easily by only orthogonal transformations without computing any eigendecomposition and singular value decomposition (SVD), consequently, our new implementation is eigendecomposition-free and SVD-free; (ii) its main computational complexity is from a economic QR factorization of the data matrix and a economic QR factorization of a n×n matrix with column pivoting, here n is the sample size, thus our new implementation is a fast one. The effectiveness of our new implementation is demonstrated by some real-world data sets. © 2009 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.patcog.2009.10.004
dc.sourceScopus
dc.subjectDimensionality reduction
dc.subjectLinear discriminant analysis
dc.subjectNull space based linear discriminant analysis
dc.subjectQR factorization
dc.subjectSingular value decomposition
dc.typeArticle
dc.contributor.departmentTEMASEK LABORATORIES
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1016/j.patcog.2009.10.004
dc.description.sourcetitlePattern Recognition
dc.description.volume43
dc.description.issue4
dc.description.page1373-1379
dc.description.codenPTNRA
dc.identifier.isiut000274954100015
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