High-dimensional Data Analysis - Couverture souple

Francois, Damien

Couverture souple

ISBN 10 : 3836493098 ISBN 13 : 9783836493093

Editeur : VDM Verlag Dr. Mueller E.K., 2008

Synopsis

High-dimensional data are everywhere: texts, sounds, spectra, images, etc. However, many data ysis tools (coming from statistics, artificial intelligence, etc.) were designed for low-dimensional data. Many of the assumptions behind data ysis 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 ysis 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 partiarly on spectral data, with the objective of inferring a physical or chemical property of a material by ysis the spectrum of the light it reflects.

Détails de l'édition

• Éditeur: VDM Verlag Dr. Mueller E.K.
• Date d'édition: 2008
• Langue: anglais
• ISBN 10: 3836493098
• ISBN 13: 9783836493093
• Reliure: Broché
• Nombre de pages: 176
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible