Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction
	Nie, Feiping 1; Xiang, Shiming2 ; Liu, Yun 3; Hou, Chenping 1; Zhang, Changshui 1
发表期刊	PATTERN RECOGNITION LETTERS
	2012-04-01
卷号	33 期号:5 页码:485-491
文章类型	Article
摘要	In this paper, a new discriminant analysis for feature extraction is derived from the perspective of least squares regression. To obtain great discriminative power between classes, all the data points in each class are expected to be regressed to a single vector, and the basic task is to find a transformation matrix such that the squared regression error is minimized. To this end, two least squares discriminant analysis methods are developed under the orthogonal or the uncorrelated constraint. We show that the orthogonal least squares discriminant analysis is an extension to the null space linear discriminant analysis, and the uncorrelated least squares discriminant analysis is exactly equivalent to the traditional linear discriminant analysis. Comparative experiments show that the orthogonal one is more preferable for real world applications. (C) 2011 Elsevier B.V. All rights reserved.
关键词	Least Squares Subspace Learning Discriminant Analysis Feature Extraction Image Recognition
WOS标题词	Science & Technology ; Technology
关键词[WOS]	FACE RECOGNITION ; PRESERVING PROJECTIONS ; REGRESSION ; REDUCTION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000301212400001
引用统计	被引频次：50[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3723
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
作者单位	1.Tsinghua Univ, Dept Automat, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China 3.Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
推荐引用方式 GB/T 7714	Nie, Feiping,Xiang, Shiming,Liu, Yun,et al. Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction[J]. PATTERN RECOGNITION LETTERS,2012,33(5):485-491.
APA	Nie, Feiping,Xiang, Shiming,Liu, Yun,Hou, Chenping,&Zhang, Changshui.(2012).Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction.PATTERN RECOGNITION LETTERS,33(5),485-491.
MLA	Nie, Feiping,et al."Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction".PATTERN RECOGNITION LETTERS 33.5(2012):485-491.