Kernel Based Algorithms for Mining Huge Data Sets Supervised, Semi-supervised, and Unsupervised Learning /

"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets by using support vector machines (SVMs) in...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Huang, Te-Ming (Autor), Kecman, Vojislav (Autor), Kopriva, Ivica (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Studies in Computational Intelligence, 17
Temas:
Data mining.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Data Mining and Knowledge Discovery.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Support Vector Machines in Classification and Regression - An Introduction
  • Iterative Single Data Algorithm for Kernel Machines from Huge Data Sets: Theory and Performance
  • Feature Reduction with Support Vector Machines and Application in DNA Microarray Analysis
  • Semi-supervised Learning and Applications
  • Unsupervised Learning by Principal and Independent Component Analysis.

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