Kernel Methods for Pattern Analysis by John Shawe-Taylor (English) Hardcover Boo

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

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.

FORMAT
Hardcover LANGUAGE
English CONDITION
Brand New Publisher Description

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.

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.

Review

'Kernel methods form an important aspect of modern pattern analysis, and this book gives a lively and timely account of such methods. ... if you want to get a good idea of the current research in this field, this book cannot be ignored.' SIAM Review '... the book provides an excellent overview of this growing field. I highly recommend it to those who are interested in pattern analysis and machine learning, and especailly to those who want to apply kernel-based methods to text analysis and bioinformatics problems.' Computing Reviews ' ... I enjoyed reading this book and am happy about is addition to my library as it is a valuable practitioner's reference. I especially liked the presentation of kernel-based pattern analysis algorithms in terse mathematical steps clearly identifying input data, output data, and steps of the process. The accompanying Matlab code or pseudocode is al extremely useful.' IAPR Newsletter

Promotional

A unique account of developing topic in data mining and machine learning.

Long Description

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.

Review Quote

"The book provides an excellent overview of this growing field. I highly recommend it to those who are interested in pattern analysis and machine learning, and especially to those who want to apply kernel-based methods to text analysis and bioinformatics problems." Computing Reviews

Promotional \"Headline\"

A unique account of developing topic in data mining and machine learning.

Description for Bookstore

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.

Description for Library

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.

Details ISBN0521813972 Author Nello Cristianini Short Title KERNEL METHODS FOR PATTERN ANA Publisher Cambridge University Press Language English ISBN-10 0521813972 ISBN-13 9780521813976 Media Book Format Hardcover Year 2004 Imprint Cambridge University Press Place of Publication Cambridge Country of Publication United Kingdom Affiliation University of California, Davis DOI 10.1604/9780521813976 UK Release Date 2004-06-28 AU Release Date 2004-06-28 NZ Release Date 2004-06-28 Pages 478 Publication Date 2004-06-28 Alternative 9780511809682 DEWEY 006.4 Illustrations 6 Tables, unspecified Audience Professional & Vocational Country of Origin US Product Class Description Software Packages
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