Wentworth
Institute of Technology
Kernel methods for pattern analysis /
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 i...
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| Main Author: | |
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| Other Authors: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge, UK ; New York :
Cambridge University Press,
2004.
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| Subjects: | |
| Online Access: |
Full text (Wentworth users only) |
| Local Note: | ProQuest Ebook Central |
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| 100 | 1 | |a Shawe-Taylor, John. | |
| 245 | 1 | 0 | |a Kernel methods for pattern analysis / |c John Shawe-Taylor, Nello Cristianini. |
| 260 | |a Cambridge, UK ; |a New York : |b Cambridge University Press, |c 2004. | ||
| 300 | |a 1 online resource (xiv, 462 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file | ||
| 504 | |a Includes bibliographical references (pages 450-459) and index. | ||
| 505 | 0 | |a Cover; Half-title; Title; Copyright; Contents; Code fragments; Preface; 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; Appendix A Proofs omitted from the main text; A.1 Proof of McDiarmid's theorem. | |
| 520 | |a 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. | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central College Complete | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Algorithms. | |
| 650 | 0 | |a Kernel functions. | |
| 650 | 0 | |a Pattern perception |x Data processing. | |
| 650 | 0 | |a Computer algorithms. | |
| 650 | 2 | |a Algorithms | |
| 650 | 2 | |a Machine Learning | |
| 650 | 7 | |a algorithms. |2 aat | |
| 700 | 1 | |a Cristianini, Nello. | |
| 758 | |i has work: |a Kernel methods for pattern analysis (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGP4fXW7MjKymFyF4fJ8kC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Shawe-Taylor, John. |t Kernel methods for pattern analysis. |d Cambridge, UK ; New York : Cambridge University Press, 2004 |z 0521813972 |w (DLC) 2003069590 |w (OCoLC)53926734 |
| 852 | |b Ebooks |h ProQuest | ||
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