High-dimensional Data Analysis : From Optimal Metrics to Feature Selection

Language: English

Published by VDM Verlag Dr. Müller, VDM Verlag Dr. Müller E.K., 2008

3836493098 / 9783836493093

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Softcover

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Neuware - High-dimensional data are everywhere: texts, sounds, spectra, images, etc. However, many data analysis tools (coming from statistics, artificial intelligence, etc.) were designed for low-dimensional data. Many of the assumptions behind data analysis tools are not transposable to high-dimensional data. For instance, the Euclidean distance concentrates in high-dimensional spaces; all distances seem identical! It furthermore does not distinguish between relenvant and irrelevant features. In Part One of the book, the phenomenon of the concentration of the distances is considered, and its consequences on data analysis tools are studied. Part Two focuses on the problem of feature selection in the case of a large number of initial features. Most of the concepts studied and presented in this thesis are illustrated on chemometric data, and more particularly on spectral data, with the objective of inferring a physical or chemical property of a material by analysis the spectrum of the light it reflects.…

Seller Inventory # 9783836493093

Title
High-dimensional Data Analysis : From Optimal Metrics to Feature Selection
Author
Damien François
Publisher
VDM Verlag Dr. Müller, VDM Verlag Dr. Müller E.K.
Publication year
2008
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3836493098
ISBN 13
9783836493093
Item weight
280 grams
Dimensions
220x150x11 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

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