Dec 1, 2008 · It is found that the discriminant power of 2DLDA is weaker than that of LDA when the same reduction dimension is considered.
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many ap- plications ...
Aug 5, 2008 · The PCA + LDA method (Belhumeur et al., 1997) is one of the most popular methods, whose idea is to ap- ply PCA to reduce the dimension of data ...
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In this paper, we further analyze the 2DLDA method and derive the upper bound of its criterion. Based on this upper bound, we show that the discriminant power ...
Two-Dimensional Linear Discriminant Analysis - NIPS papers
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In this paper, we propose a novel LDA algorithm, namely 2DLDA, which stands for 2-Dimensional Linear Discriminant Analysis.
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Dec 1, 2008 · 2DLDA and its variants have attracted much attention from researchers recently due to the advantages over the singularity problem and the ...
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications ...
A note on two-dimensional linear discriminant analysis Check holdings at Shatin Storage Serials (Back issues) (Shatin) (TK7882.P3 P396).
a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events.
Abstract—Recent advances show that two-dimensional linear discriminant analysis (2DLDA) is a successful matrix based di- mensionality reduction method.