Kernel Methods for Pattern Analysis

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Cambridge University Press, Jun 28, 2004 - Computers - 462 pages
3 Reviews
This book fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to be implemented, suitable for standard pattern discovery problems in field 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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Review: Kernel Methods for Pattern Analysis

User Review  - Michiel - Goodreads

Very clearly written background manual about the different kernel-based algorithms and the different kernels for specific tasks. The derivations of generalisation bound where the most lucid I have ever encountered. Read full review

Contents

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Copyright

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Page 453 - Canonical correlation analysis; an overview with application to learning methods," Technical Report CSD-TR-03-02, Dept.

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About the author (2004)

Nello Cristianini is a Professor of Artificial Intelligence, University of Bristol.

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