Principal Manifolds for Data Visualization and Dimension Reduction (Lecture Notes in Computational Science and Engineering)

Principal Manifolds for Data Visualization and Dimension Reduction (Lecture Notes in Computational Science and Engineering)

by Donald C . Wunsch (Editor), Alexander N . Gorban (Editor), Balázs Kégl (Editor), Andrei Zinovyev (Editor)

Synopsis

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.

$232.60

Quantity

10 in stock

More Information

Format: Paperback
Pages: 364
Edition: illustrated edition
Publisher: Springer
Published: 01 Oct 2007

ISBN 10: 3540737499
ISBN 13: 9783540737490