Support Vector Machines for Pattern Classification
Seiten
2005
|
Edition. ed.
Springer London Ltd (Verlag)
978-1-85233-929-6 (ISBN)
Springer London Ltd (Verlag)
978-1-85233-929-6 (ISBN)
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Support Vector Machines are popular because of their high classification importance; this book focuses on the discussions on SVMs specifically to pattern classification.
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.
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.
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.
| Erscheint lt. Verlag | 25.8.2005 |
|---|---|
| Reihe/Serie | Advances in Computer Vision and Pattern Recognition |
| Zusatzinfo | 110 black & white illustrations, 54 black & white tables |
| Verlagsort | England |
| Sprache | englisch |
| Maße | 234 x 156 mm |
| Gewicht | 1500 g |
| Einbandart | gebunden |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-10 | 1-85233-929-2 / 1852339292 |
| ISBN-13 | 978-1-85233-929-6 / 9781852339296 |
| Zustand | Neuware |
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