Support Vector Machines for Pattern Classification (eBook, PDF) - Abe, Shigeo
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  • Format: PDF


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…mehr

Produktbeschreibung
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. TOC:Introduction.- Two-class Support Vector Machines.- Multiclass Support Vector Machines.- Variants of Support Vector Machines.- Training Methods.- Feature Selection and Extraction.- Clustering.- Kernel-Based Methods.- Maximum Margin Multilayer Neural Networks.- Maximum Margin Fuzzy Classifiers.- Function Approximation.- Conventional Classifiers.- Matrices.

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  • Produktdetails
  • Verlag: Springer-Verlag GmbH
  • Erscheinungstermin: 30. März 2006
  • Englisch
  • ISBN-13: 9781846282195
  • Artikelnr.: 37355333
Inhaltsangabe
IntroductionTwo-Class Support Vector MachinesMulticlass Support Vector MachinesVariants of Support Vector MachinesTraining MethodsKernel-Based MethodsFeature Selection and ExtractionClusteringMaximum-Margin Multilayer Neural NetworksMaximum-Margin Fuzzy ClassifiersFunction Approximation.

IntroductionTwo-Class Support Vector MachinesMulticlass Support Vector MachinesVariants of Support Vector MachinesTraining MethodsKernel-Based MethodsFeature Selection and ExtractionClusteringMaximum-Margin Multilayer Neural NetworksMaximum-Margin Fuzzy ClassifiersFunction Approximation.
Rezensionen
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)