Nonlinear Dimensionality Reduction

Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principal component analysis and classical metric multidimensional scaling suffer from being based on linear models. Until recently, very few methods were able t...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Lee, John A. (Autor), Verleysen, Michel (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Information Science and Statistics,
Temas:
Mathematical logic.
Computer science-Mathematics.
Mathematical statistics.
Data mining.
Information visualization.
Computer vision.
Pattern recognition systems.
Mathematical Logic and Foundations.
Probability and Statistics in Computer Science.
Data Mining and Knowledge Discovery.
Data and Information Visualization.
Computer Vision.
Automated Pattern Recognition.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • High-Dimensional Data
  • Characteristics of an Analysis Method
  • Estimation of the Intrinsic Dimension
  • Distance Preservation
  • Topology Preservation
  • Method comparisons
  • Conclusions.

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