Fisher's Linear Discriminant Analysis With Space-Folding Operations

Fisher's linear discriminant analysis (LDA) is an easy-to-use supervised dimensionality reduction method. However, LDA may be ineffective against complicated class distributions. It is well-known that deep feedforward neural networks with rectified linear units as activation functions can map m...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2023-07, Vol.45 (7), p.1-8
1. Verfasser:	Chang, Chin-Chun
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Classification Composition Covariance matrices Discriminant analysis Eigenvalues and eigenfunctions Feature extraction Feedforward neural networks Fisher's linear discriminant analysis Folding Kernel Linear discriminant analysis rectified linear units space-folding operations Training
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