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Kernel methods for pattern analysis

Author: John Shawe-Taylor; Nello Cristianini
Publisher: Cambridge : Cambridge University Press, 2004.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
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. (Midwest).
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Genre/Form: Matériel didactique
Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: John Shawe-Taylor; Nello Cristianini
ISBN: 0521813972 9780521813976
OCLC Number: 300293207
Notes: EX. 1, Réimpression 2006.
Description: xiv, 462 p. : illustrations ; 26 cm
Contents: 1. Pattern analysis --
2. Kernel methods : an overview --
3. Properties of kernels --
4. Detecting stable patterns --
5. Elementary algorithms in feature space --
6. Pattern analysis using eigen-decompositions --
7. Pattern analysis using convex optimisation --
8. Ranking, clustering and data visualisation --
9. Basic kernels and kernel types --
10. Kernels for text --
11. Kernels for structured data : strings, trees, etc. --
12. Kernels from generative models --
App. A. Proofs omitted from the main text --
App. B. Notational conventions --
App. C. List of pattern analysis methods --
App. D. List of kernels.
Responsibility: John Shawe-Taylor, Nello Cristianini.
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A unique account of developing topic in data mining and machine learning.  Read more...

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'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 Read more...

 
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