Synopsis
This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software make it an ideal starting point for further study.
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Book Description
This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications.
Review
"This book is an excellent introduction to this area... it is nicely organized, self-contained, and well written. The book is most suitable for the beginning graduate student in computer science." Richard A Chechile, Journal of Mathematical Psychology
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- PublisherCambridge University Press
- Publication date2000
- ISBN 10 0521780195
- ISBN 13 9780521780193
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages204
- Rating
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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