Complexity-reduced implementations of complete and null-space-based linear discriminant analysis

DOI10.1016/j.neunet.2013.05.010zbMath1296.62133OpenAlexW2043223282WikidataQ51201572 ScholiaQ51201572MaRDI QIDQ461149

Wenming Zheng, Gui-Fu Lu

Publication date: 10 October 2014

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2013.05.010

zbMATH Keywords

feature extractiondimensionality reductionsmall sample size problemcomplete linear discriminant analysisnull-space-based linear discriminant analysis

Mathematics Subject Classification ID

Related Items (1)

A theoretical contribution to the fast implementation of null linear discriminant analysis with random matrix multiplication

Uses Software

• PRMLT

Cites Work

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• A new perspective to null linear discriminant analysis method and its fast implementation using random matrix multiplication with scatter matrices
• Incremental complete LDA for face recognition
• Regularized orthogonal linear discriminant analysis
• A new and fast implementation for null space based linear discriminant analysis
• A New and Fast Orthogonal Linear Discriminant Analysis on Undersampled Problems
• Structure Preserving Dimension Reduction for Clustered Text Data Based on the Generalized Singular Value Decomposition
• Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
• Discriminant Analysis with Singular Covariance Matrices: Methods and Applications to Spectroscopic Data
• Using Linear Algebra for Intelligent Information Retrieval
• Face recognition based on the uncorrelated discriminant transformation
• A theorem on the uncorrelated optimal discriminant vectors

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