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

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9780521780193: An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

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.

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Recensione:

'… 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

Descrizione del libro:

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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1.

Nello Christianini, John Shawe-Taylor, Nello Cristianini
Editore: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2000. Hardback. Condizione libro: 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. Codice libro della libreria KNV9780521780193

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Nello Christianini, John Shawe-Taylor, Nello Cristianini
Editore: Cambridge University Press
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press. Hardback. Condizione libro: new. BRAND NEW PRINT ON DEMAND., 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. Codice libro della libreria B9780521780193

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3.

Nello Christianini, John Shawe-Taylor, Nello Cristianini
Editore: Cambridge University Press 2000-03-23, Cambridge (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press 2000-03-23, Cambridge, 2000. hardback. Condizione libro: New. Codice libro della libreria 9780521780193

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Nello Christianini, John Shawe-Taylor, Nello Cristianini
Editore: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2000. Hardback. Condizione libro: 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. Codice libro della libreria KNV9780521780193

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NELLO CRISTIANINI , JOHN SHAWE-TAYLOR
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro 2000. Hardback. Condizione libro: NEW. 9780521780193 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Codice libro della libreria HTANDREE0475396

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Cristianini, Nello
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ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press, 2000. HRD. Condizione libro: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria I1-9780521780193

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Nello Christianini
Editore: Cambridge University Press Mrz 2000 (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press Mrz 2000, 2000. Buch. Condizione libro: Neu. 252x174x15 mm. Neuware - 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. 204 pp. Englisch. Codice libro della libreria 9780521780193

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Cristianini, Nello
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ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press, 2000. HRD. Condizione libro: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria I1-9780521780193

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Cristianini, Nello
Editore: Cambridge University Press (2016)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press, 2016. Paperback. Condizione libro: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Codice libro della libreria ria9780521780193_lsuk

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Nello Christianini
Editore: Cambridge University Press Mrz 2000 (2000)
ISBN 10: 0521780195 ISBN 13: 9780521780193
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Descrizione libro Cambridge University Press Mrz 2000, 2000. Buch. Condizione libro: Neu. 252x174x15 mm. Neuware - 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. 204 pp. Englisch. Codice libro della libreria 9780521780193

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