Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition) - Tapa dura

Abe, Schigeo

 
9781852339296: Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
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ISBN 10: 1852339292 ISBN 13: 9781852339296
Editorial: Springer Verlag, 2005

Sinopsis

Support vector machines (SVMs), were originally formulated for two-class classification problems, and have been accepted as a powerful tool for developing pattern classification and function approximations systems. This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects. The book clarifies the characteristics of two-class SVMs through their extensive analysis, presents various useful architectures for multiclass classification and function approximation problems, and discusses kernel methods for improving generalization ability of conventional neural networks and fuzzy systems. Ample illustrations, examples and computer experiments are included to help readers understand the new ideas and their usefulness. This book supplies a comprehensive resource for the use of SVMs in pattern classification and will be invaluable reading for researchers, developers & students in academia and industry.

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Críticas

From the reviews: "This broad and deep ... book is organized around the highly significant concept of pattern recognition by support vector machines (SVMs). ... The book is praxis and application oriented but with strong theoretical backing and support. Many ... details are presented and discussed, thereby making the SVM both an easy-to-understand learning machine and a more likable data modeling (mining) tool. Shigeo Abe has produced the book that will become the standard ... . I like it and therefore highly recommend this book ... ." (Vojislav Kecman, SIAM Review, Vol. 48 (2), 2006)

Reseña del editor

Support vector machines (SVMs), were originally formulated for two-class classification problems, and have been accepted as a powerful tool for developing pattern classification and function approximations systems. This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects. The book clarifies the characteristics of two-class SVMs through their extensive analysis, presents various useful architectures for multiclass classification and function approximation problems, and discusses kernel methods for improving generalization ability of conventional neural networks and fuzzy systems. Ample illustrations, examples and computer experiments are included to help readers understand the new ideas and their usefulness. This book supplies a comprehensive resource for the use of SVMs in pattern classification and will be invaluable reading for researchers, developers & students in academia and industry.

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Editorial
Springer Verlag
Año de publicación
2005
Idioma
Inglés
ISBN 10 
1852339292
ISBN 13 
9781852339296
Encuadernación
Tapa dura
Número de páginas
358
Contacto del fabricante
no disponible
Persona responsable
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Alemania

Otras ediciones populares con el mismo título

9781849969635: Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)

Edición Destacada

ISBN 10:  1849969639 ISBN 13:  9781849969635
Editorial: Springer London Ltd, 2010
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