SOM: Stochastic initialization versus principal components

Selection of a good initial approximation is a well known problem for all iterative methods of data approximation, from k-means to Self-Organizing Maps (SOM) and manifold learning. The quality of the resulting data approximation depends on the initial approximation. Principal components are popular...

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Veröffentlicht in:	Information sciences 2016-10, Vol.364-365, p.213-221
Hauptverfasser:	Akinduko, Ayodeji A., Mirkes, Evgeny M., Gorban, Alexander N.
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximation Benchmark test Learning Manifold learning Manifolds Mathematical analysis Mathematical models Nonlinearity PCA Random initiation Reproducibility SOM
Online-Zugang:	Volltext
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