Kernel Methods for Pattern Analysis - John Shawe-Taylor, Nello Cristianini

Kernel Methods for Pattern Analysis

Buch | Hardcover
478 Seiten
2004
Cambridge University Press (Verlag)
978-0-521-81397-6 (ISBN)
108,45 inkl. MwSt
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The kernel functions methodology described here provides a powerful and unified framework for disciplines ranging from neural networks and pattern recognition to machine learning and data mining. This book provides practitioners with a large toolkit of algorithms, kernels and solutions ready to be implemented, suitable for standard pattern discovery problems.
Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed from lectures and tutorials, fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to use for standard pattern discovery problems in fields such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.

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Preface; Part I. Basic Concepts: 1. Pattern analysis; 2. Kernel methods: an overview; 3. Properties of kernels; 4. Detecting stable patterns; Part II. Pattern Analysis Algorithms: 5. Elementary algorithms in feature space; 6. Pattern analysis using eigen-decompositions; 7. Pattern analysis using convex optimisation; 8. Ranking, clustering and data visualisation; Part III. Constructing Kernels: 9. Basic kernels and kernel types; 10. Kernels for text; 11. Kernels for structured data: strings, trees, etc.; 12. Kernels from generative models; Appendix A: proofs omitted from the main text; Appendix B: notational conventions; Appendix C: list of pattern analysis methods; Appendix D: list of kernels; References; Index.

Erscheint lt. Verlag 28.6.2004
Zusatzinfo 6 Tables, unspecified
Verlagsort Cambridge
Sprache englisch
Maße 170 x 249 mm
Gewicht 1000 g
Themenwelt Informatik Office Programme Outlook
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 0-521-81397-2 / 0521813972
ISBN-13 978-0-521-81397-6 / 9780521813976
Zustand Neuware
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