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In den WarenkorbZustand: New. pp. 461.
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In den WarenkorbPaperback. Zustand: Brand New. 461 pages. 9.25x6.14x1.02 inches. In Stock.
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In den WarenkorbKartoniert / Broschiert. Zustand: New. Emmanuel Barillot, Laurence Calzone, Philippe Hupe, Jean-Philippe Vert, and Andrei Zinovyev are all with the Institut Curie in Paris, France.The future of cancer research and the development of new therapeutic strategies rely on our abilit.
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Paperback. Zustand: Very Good. 2008. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 423 pages. 9.75x6.50x1.00 inches. In Stock.
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In den WarenkorbZustand: New. pp. 364 Illus.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Principal Manifolds for Data Visualization and Dimension Reduction | Alexander N. Gorban (u. a.) | Taschenbuch | Lecture Notes in Computational Science and Engineering | xxiv | Englisch | 2007 | Springer | EAN 9783540737490 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, Springer Spektrum, 2007
ISBN 10: 3540737499 ISBN 13: 9783540737490
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SOM), etc. 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 as well. Presentation of algorithms is supplemented by case studies, from engineering to astronomy, but mostly of biological data: analysis of microarray and metabolite data. The volume ends with a tutorial 'PCA and K-meansdecipher genome'. The book is meant to be useful for practitioners in applied data analysis in life sciences, engineering, physics and chemistry; it will also be valuable to PhD students and researchers in computer sciences, applied mathematics and statistics.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 1st edition. 334 pages. 9.00x6.00x0.50 inches. In Stock.