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Principal Manifolds for Data Visualization and Dimension Reduction (Paperback)

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Product Overview

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. Presentation of algorithms is supplemented by case studies. The volume ends with a tutorial PCA deciphers genome.

Specifications

Publisher Springer Verlag
Mfg Part# 9783540737490
SKU 206166024
Format Paperback
ISBN10 3540737499
Release Date 8/13/2012
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