An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Autor Nello Cristianini, John Shawe-Tayloren Limba Engleză Hardback – 22 mar 2000
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Specificații
ISBN-13: 9780521780193
ISBN-10: 0521780195
Pagini: 204
Ilustrații: 12 b/w illus. 5 colour illus. 25 exercises
Dimensiuni: 175 x 249 x 15 mm
Greutate: 0.5 kg
Ediția:New.
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:Cambridge, United Kingdom
ISBN-10: 0521780195
Pagini: 204
Ilustrații: 12 b/w illus. 5 colour illus. 25 exercises
Dimensiuni: 175 x 249 x 15 mm
Greutate: 0.5 kg
Ediția:New.
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:Cambridge, United Kingdom
Cuprins
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.
Recenzii
'… 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
'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
Descriere
This is a comprehensive introduction to Support Vector Machines, a generation learning system based on advances in statistical learning theory.