Kernel Methods For Pattern Analysis by John Shawe-TaylorKernel Methods For Pattern Analysis by John Shawe-Taylor

Kernel Methods For Pattern Analysis

byJohn Shawe-Taylor, Nello Cristianini

Hardcover | June 28, 2004

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This book provides professionals with a large selection of algorithms, kernels and solutions ready for implementation and suitable for standard pattern discovery problems in fields such as bioinformatics, text analysis and image analysis. It also serves as an 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.
Title:Kernel Methods For Pattern AnalysisFormat:HardcoverDimensions:474 pages, 9.72 × 6.85 × 1.14 inPublished:June 28, 2004Publisher:Cambridge University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0521813972

ISBN - 13:9780521813976


Table of Contents

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.

Editorial Reviews

"If you are interested in an introduction to statistical techniques for analyzing text documents, Kernel Methods will serve you well."
M. Last, Journal of the American Statistical Association