Support vector machines

Vector Page 1 An Introduction to Mello cristianini John Shawe-Taylor Support Vector Machines and other kernel-based earning methods Page 2 Contents Preface ix Notation xiii t The Learning Methodology 1 11 Supervised Learning 1 1.2 Learning and Generalisation 3 1.3 Improving Generalisation 4 1.4 Attractions and Drawbacks of Learning 6 1.5 Support Vector Machines for Learning 7 1.6 Exercises 7 1.7 Further Reading and Advanced Topics S 2 Linear Learning Machines 9 2.1 Linear Classification 9 2.1.1 Rosenblatt's Perceptron 11 2.1.2 Other Linear Classifiers 19 2.1.3 Multi-class Discrimination 20 2.2 Linear Regression 20 2.21 Least Squares 21 2.2.2 Ridge Regression 22 2.3 Dual Representation of Linear Machines 24 2.4 Exercises 25 2.5 Further Reading and Advanced Topics 25 3 kernel-Induced Feature Spaces 26 3.1 Learning in Feature Space 27 3.2 The Implicit Mapping into Feature Space 30 3.3 …