Buch, Englisch, 309 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 654 g
Buch, Englisch, 309 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 654 g
Reihe: Information Science and Statistics
ISBN: 978-0-387-39350-6
Verlag: Springer
This book describes established and advanced methods for reducing the dimensionality of numerical databases. Each description starts from intuitive ideas, develops the necessary mathematical details, and ends by outlining the algorithmic implementation. The text provides a lucid summary of facts and concepts relating to well-known methods as well as recent developments in nonlinear dimensionality reduction. Methods are all described from a unifying point of view, which helps to highlight their respective strengths and shortcomings. The presentation will appeal to statisticians, computer scientists and data analysts, and other practitioners having a basic background in statistics or computational learning.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik Mathematik Mathematik Allgemein Mathematische Logik
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenkompression, Dokumentaustauschformate
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik Mathematik Mathematik Interdisziplinär Computeralgebra
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Grafikprogrammierung
Weitere Infos & Material
High-Dimensional Data.- Characteristics of an Analysis Method.- Estimation of the Intrinsic Dimension.- Distance Preservation.- Topology Preservation.- Method comparisons.- Conclusions.
