Support Vector Machines: Theory and Applications

The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Ma...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Wang, Lipo (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005.
Edición:1st ed. 2005.
Colección:Studies in Fuzziness and Soft Computing, 177
Temas:
Computer science.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Pattern recognition systems.
Theory of Computation.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Automated Pattern Recognition.
Acceso en línea:Texto Completo
Descripción
Sumario:The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in the respective fields.
Descripción Física:X, 431 p. online resource.
ISBN:9783540323846
ISSN:1860-0808 ;

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