Book contents
- Frontmatter
- Contents
- Preface
- Notation
- 1 The Learning Methodology
- 2 Linear Learning Machines
- 3 Kernel-Induced Feature Spaces
- 4 Generalisation Theory
- 5 Optimisation Theory
- 6 Support Vector Machines
- 7 Implementation Techniques
- 8 Applications of Support Vector Machines
- A Pseudocode for the SMO Algorithm
- B Background Mathematics
- References
- Index
Contents
Published online by Cambridge University Press: 05 March 2013
- Frontmatter
- Contents
- Preface
- Notation
- 1 The Learning Methodology
- 2 Linear Learning Machines
- 3 Kernel-Induced Feature Spaces
- 4 Generalisation Theory
- 5 Optimisation Theory
- 6 Support Vector Machines
- 7 Implementation Techniques
- 8 Applications of Support Vector Machines
- A Pseudocode for the SMO Algorithm
- B Background Mathematics
- References
- Index
Summary
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- Type
- Chapter
- Information
- Publisher: Cambridge University PressPrint publication year: 2000