A General Matrix Function Dimensionality Reduction Framework and Extension for Manifold Learning

Many dimensionality reduction methods in the manifold learning field have the so-called small-sample-size (SSS) problem. Starting from solving the SSS problem, we first summarize the existing dimensionality reduction methods and construct a unified criterion function of these methods. Then, combinin...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 52; H. 4; S. 2137 - 2148
Hauptverfasser:	Ran, Ruisheng, Feng, Ji, Zhang, Shougui, Fang, Bin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Criteria Cybernetics Dimensionality reduction Handwriting Hyperbolic functions Laplace equations Learning systems Linear functions Machine learning manifold learning Manifolds Manifolds (mathematics) Mathematical analysis matrix function Pattern classification Principal component analysis Reduction small-sample-size (SSS) problem
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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