An Introduction to Support Vector Machines and Other Kernel-based Learning Methods Hardback

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9780521780193: An Introduction to Support Vector Machines and Other Kernel-based Learning Methods Hardback
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Support Vector Machines are now established as one of the standard tools for machine learning and data mining. Students will find this introduction both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications.

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Críticas:

'... the most accessible introduction to the area I have yet seen'. D. J. Hand, Publication of the International Statistical Institute

'The book is an admirable presentation of this powerful new approach to pattern classification.' Alex M. Andrew, Robotica

' ... an excellent book, complete and readable without big requirements in mathematical functional analysis.' Zentralblatt für Mathematik und ihre Grenzgebiete Mathematics Abstracts

Product Description:

Book by Cristianini Nello ShaweTaylor John

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Cristianini, Nello
Publicado por Cambridge University Press (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press, 2000. HRD. Condición: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: IQ-9780521780193

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Nello Cristianini, John Shawe-Taylor
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ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2015. Hardback. Condición: New. Repr.. Language: English . Brand New Book. This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software. Nº de ref. del artículo: KNV9780521780193

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Nello Cristianini, John Shawe-Taylor
Publicado por CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2015)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2015. Hardback. Condición: New. Repr.. Language: English . Brand New Book. This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software. Nº de ref. del artículo: KNV9780521780193

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Nello Cristianini (author), John Shawe-Taylor (author)
Publicado por Cambridge University Press 2000-03-23, Cambridge (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press 2000-03-23, Cambridge, 2000. hardback. Condición: New. Nº de ref. del artículo: 9780521780193

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Cristianini, Nello
Publicado por Cambridge University Press (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press, 2000. HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: IQ-9780521780193

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Nello Cristianini, John Shawe-Taylor
Publicado por Cambridge University Press (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press, 2000. Hardcover. Condición: New. 1. Nº de ref. del artículo: DADAX0521780195

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Nello Cristianini/ John Shawe-Taylor
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Descripción Cambridge Univ Pr, 2000. Hardcover. Condición: Brand New. 1st edition. 189 pages. 10.25x7.25x0.75 inches. In Stock. Nº de ref. del artículo: __0521780195

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Cristianini, Nello
Publicado por Cambridge University Press (2018)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press, 2018. Hardcover. Condición: New. Never used! This item is printed on demand. Nº de ref. del artículo: 0521780195

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Cristianini, Nello / Shawe-Taylor, John
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Condición: New. Publisher/Verlag: Cambridge University Press | A comprehensive introduction to this recent method for machine learning and data mining. | This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software. Support Vector Machines are now established as one of the standard tools for machine learning and data mining. Students will find this introduction both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. | Preface; 1. The learning methodology; 2. Linear learning machines; 3. Kernel-induced feature spaces; 4. Generalisation theory; 5. Optimisation theory; 6. Support vector machines; 7. Implementation techniques; 8. Applications of support vector machines; Appendix A: pseudocode for the SMO algorithm; Appendix B: background mathematics; Appendix C: glossary; Appendix D: notation; Bibliography; Index. | Format: Hardback | Language/Sprache: english | 523 gr | 189 pp. Nº de ref. del artículo: K9780521780193

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NELLO CRISTIANINI , JOHN SHAWE-TAYLOR
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción 2000. Hardback. Condición: NEW. 9780521780193 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. For all enquiries, please contact Herb Tandree Philosophy Books directly - customer service is our primary goal. Nº de ref. del artículo: HTANDREE0475396

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