Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.patcog.2009.10.004
Title: A new and fast implementation for null space based linear discriminant analysis
Authors: Chu, D. 
Thye, G.S. 
Keywords: Dimensionality reduction
Linear discriminant analysis
Null space based linear discriminant analysis
QR factorization
Singular value decomposition
Issue Date: Apr-2010
Citation: Chu, 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
Abstract: In 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.
Source Title: Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/115561
ISSN: 00313203
DOI: 10.1016/j.patcog.2009.10.004
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

43
checked on Dec 13, 2018

WEB OF SCIENCETM
Citations

35
checked on Nov 27, 2018

Page view(s)

63
checked on Nov 2, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.