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Learning Regularized LDA by Clustering
Pang, Yanwei1; Wang, Shuang1; Yuan, Yuan2
作者部门光学影像学习与分析中心
2014-12-01
发表期刊IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X
卷号25期号:12页码:2191-2201
产权排序2
摘要As a supervised dimensionality reduction technique, linear discriminant analysis has a serious overfitting problem when the number of training samples per class is small. The main reason is that the between-and within-class scatter matrices computed from the limited number of training samples deviate greatly from the underlying ones. To overcome the problem without increasing the number of training samples, we propose making use of the structure of the given training data to regularize the between- and within-class scatter matrices by between-and within-cluster scatter matrices, respectively, and simultaneously. The within-and between-cluster matrices are computed from unsupervised clustered data. The within-cluster scatter matrix contributes to encoding the possible variations in intraclasses and the between-cluster scatter matrix is useful for separating extra classes. The contributions are inversely proportional to the number of training samples per class. The advantages of the proposed method become more remarkable as the number of training samples per class decreases. Experimental results on the AR and Feret face databases demonstrate the effectiveness of the proposed method.
文章类型Article
关键词Dimensionality Reduction Face Recognition Feature Extraction Linear Discriminant Analysis (Lda)
WOS标题词Science & Technology ; Technology
DOI10.1109/TNNLS.2014.2306844
收录类别SCI ; EI
关键词[WOS]LINEAR DISCRIMINANT-ANALYSIS ; FACE-RECOGNITION ; FEATURE-EXTRACTION ; DIMENSIONALITY REDUCTION ; CLASSIFICATION ; ALGORITHMS ; SELECTION
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000345518900006
引用统计
被引频次:94[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/22417
专题光谱成像技术研究室
作者单位1.Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China
2.Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China
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Pang, Yanwei,Wang, Shuang,Yuan, Yuan. Learning Regularized LDA by Clustering[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2014,25(12):2191-2201.
APA Pang, Yanwei,Wang, Shuang,&Yuan, Yuan.(2014).Learning Regularized LDA by Clustering.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,25(12),2191-2201.
MLA Pang, Yanwei,et al."Learning Regularized LDA by Clustering".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 25.12(2014):2191-2201.
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