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Principal Manifolds for Data Visualization and Dimension Reduction - Lecture Notes in Computational Science and Engineering Alexander N Gorban 2008 edition
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Principal Manifolds for Data Visualization and Dimension Reduction - Lecture Notes in Computational Science and Engineering
Alexander N Gorban
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
| Médias | Livres Paperback Book (Livre avec couverture souple et dos collé) |
| Validé | 1 octobre 2007 |
| ISBN13 | 9783540737490 |
| Éditeurs | Springer-Verlag Berlin and Heidelberg Gm |
| Pages | 340 |
| Dimensions | 155 × 235 × 13 mm · 517 g |
| Langue et grammaire | Allemand |
| Éditeur | Gorban, Alexander N. |
| Éditeur | Kegl, Balazs |
| Éditeur | Wunsch, Donald C. |
| Éditeur | Zinovyev, Andrei |
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