Principal manifolds for data visualization and dimension reduction / Alexander N. Gorban,Balázs Kégl, Donald C. Wunsch, Andrei Zinovyev, editors.

Contributor(s): Kégl, Balázs [editor] | Zinovyev. Andrei [editor] | Wunsch, Donald C [editor] | Gorbanʹ, A. N. (Aleksandr Nikolaevich) [autor]Material type: TextTextLanguage: English Series: Lecture notes in computational science and engineering ; 58Copyright date: Berlin ; New York : Springer, 2008Edition: First EditionDescription: xxiii, 334 pages : illustration (some columns) ; 24 cmISBN: 9783540737490; 3540737499Subject(s): Principal components analysis | Statistics -- Graphic methods | Mathematical statistics | Análisis de componentes principales | Estadística -- Métodos gráficos | Estadística matemáticaDDC classification: 001.4226028566
Partial contents:
Contents: Developments and applications of nolinear principal componet analysis -- a review -- Nonlinear principal component analysis: neutral network models and applications -- Learning nonlinear principal manifolds by self-organising maps -- Elastic maps and nets for approximating principal manifolds and their application to microarray data visualization -- Topology-preserving mappong for data visualisation -- The iterative extraction approach to clustering -- Representating complex data using localized principal components with application to astronomical data -- Auto - associative models, nonlinear principal component analysis, manifolds and projection pursuit -- Beyond the concept of manifolds: principal tres, metro maps, and elastic cubic complexes -- Diffusion maps - a probabilistic interpretation fpor spectral embedding and clustering algorithms -- On bounds for diffusion, discrepancy and fill distance metrics -- Gemetric optimization methods for the analysis of gene expression data -- Dimensionality reduction and microarray data -- PCA and K.Means decipher genome.
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Item type Current library Call number Copy number Status Date due Barcode Item holds
Libro académico Libro académico Biblioteca del Campus
001.4226028566 P9573 2008 (Browse shelf (Opens below)) Ej. 1 Available 001407
Libro académico Libro académico Biblioteca del Campus
001.4226028566 P9573 2008 (Browse shelf (Opens below)) Ej. 2 Available 001408
Libro académico Libro académico Biblioteca del Campus
001.4226028566 P9573 2008 (Browse shelf (Opens below)) Ej. 3 Available 001409
Total holds: 0

"This book is a collection of reviews and original papers presented partially at the workshop 'Principal manifolds for data cartography and dimension reduction' (Leicester, August 24-26, 2006)."--P. X.

Includes Index

Includes bibliographical references.

Contents: Developments and applications of nolinear principal componet analysis -- a review -- Nonlinear principal component analysis: neutral network models and applications -- Learning nonlinear principal manifolds by self-organising maps -- Elastic maps and nets for approximating principal manifolds and their application to microarray data visualization -- Topology-preserving mappong for data visualisation -- The iterative extraction approach to clustering -- Representating complex data using localized principal components with application to astronomical data -- Auto - associative models, nonlinear principal component analysis, manifolds and projection pursuit -- Beyond the concept of manifolds: principal tres, metro maps, and elastic cubic complexes -- Diffusion maps - a probabilistic interpretation fpor spectral embedding and clustering algorithms -- On bounds for diffusion, discrepancy and fill distance metrics -- Gemetric optimization methods for the analysis of gene expression data -- Dimensionality reduction and microarray data -- PCA and K.Means decipher genome.

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