A New and Fast Orthogonal Linear Discriminant Analysis on Undersampled Problems

Dimensionality reduction has become a ubiquitous preprocessing step in many applications. Linear discriminant analysis (LDA) has been known to be one of the most optimal dimensionality reduction methods for classification. However, a main disadvantage of LDA is that the so-called total scatter matri...

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Veröffentlicht in:	SIAM journal on scientific computing 2010-01, Vol.32 (4), p.2274-2297
Hauptverfasser:	Chu, Delin, Goh, Siong Thye
Format:	Artikel
Sprache:	eng
Schlagworte:	Computation Discriminant analysis Linear algebra Mathematical analysis Mathematical models Matrices Matrix Methods Optimization Reduction Studies Transformations
Online-Zugang:	Volltext
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