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SIAMMAX
2010
189views more  SIAMMAX 2010»
9 years 6 months ago
Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
Lei-Hong Zhang, Li-Zhi Liao, Michael K. Ng
TNN
2010
149views Management» more  TNN 2010»
9 years 6 months ago
A rank-one update algorithm for fast solving kernel Foley-Sammon optimal discriminant vectors
Discriminant analysis plays an important role in statistical pattern recognition. A popular method is the Foley
Wenming Zheng, Zhouchen Lin, Xiaoou Tang
PR
2008
129views more  PR 2008»
9 years 11 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park
TNN
2008
105views more  TNN 2008»
9 years 11 months ago
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Shuiwang Ji, Jieping Ye
CSDA
2004
124views more  CSDA 2004»
9 years 11 months ago
Fast and robust discriminant analysis
The goal of discriminant analysis is to obtain rules that describe the separation between groups of observations. Moreover it allows to classify new observations into one of the k...
Mia Hubert, Katrien van Driessen
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