Principal Manifolds for Data Visualization and Dimension Reduction - Lecture Notes in Computational Science and Engineering - Alexander N Gorban - Grāmatas - Springer-Verlag Berlin and Heidelberg Gm - 9783540737490 - 2007. gada 1. oktobris
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Principal Manifolds for Data Visualization and Dimension Reduction - Lecture Notes in Computational Science and Engineering 2008 edition

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The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described.


364 pages, 68 black & white illustrations, 14 colour illustrations, 22 black & white tables, biograp

Mediji Grāmatas     Paperback Book   (Grāmata ar mīksto vāku un līmēto muguru)
Izlaists 2007. gada 1. oktobris
ISBN13 9783540737490
Izdevēji Springer-Verlag Berlin and Heidelberg Gm
Lapas 340
Izmēri 155 × 235 × 13 mm   ·   517 g
Valoda Vācu  
Redaktors Gorban, Alexander N.
Redaktors Kegl, Balazs
Redaktors Wunsch, Donald C.
Redaktors Zinovyev, Andrei

Vairāk no Alexander N Gorban

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