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

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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Review:

'… 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

"Sobre este título" puede pertenecer a otra edición de este libro.

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1.

Cristianini; Shawe-Taylor
Editorial: Cambridge University Press (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
Nuevos Tapa dura Cantidad: 1
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Descripción Cambridge University Press, 2000. Hardcover. Estado de conservación: New. Nº de ref. de la librería SONG0521780195

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Cristianini; Shawe-Taylor
Editorial: Cambridge University Press
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press. Hardback. Estado de conservación: new. BRAND NEW, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, Nello Christianini, John Shawe-Taylor, Nello Cristianini, 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. de la librería B9780521780193

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Cristianini; Shawe-Taylor
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2000. Hardback. Estado de conservación: New. Repr.. 248 x 174 mm. 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. de la librería KNV9780521780193

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Cristianini; Shawe-Taylor
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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The Book Depository US
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2000. Hardback. Estado de conservación: New. Repr.. 248 x 174 mm. 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. de la librería KNV9780521780193

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Cristianini; Shawe-Taylor
Editorial: 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. Estado de conservación: New. Nº de ref. de la librería 9780521780193

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Cristianini; Shawe-Taylor
Editorial: Cambridge University Press (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press, 2000. HRD. Estado de conservación: 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. de la librería I1-9780521780193

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Cristianini; Shawe-Taylor
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ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descripción Cambridge University Press, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9780521780193_lsuk

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Cristianini; Shawe-Taylor
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Descripción Cambridge University Press, 2000. HRD. Estado de conservación: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería I1-9780521780193

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Cristianini; Shawe-Taylor
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Descripción Estado de conservación: 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. de la librería K9780521780193

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Descripción Estado de conservación: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Nº de ref. de la librería NU-ING-00308541

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