An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Editorial Reviews
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
Book Description
This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. 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 make it an ideal starting point for further study.
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods,Nello Cristianini,John Shawe-Taylor,Cambridge University Press,0521780195,Algorithms,Algorithms (Computer Programming),Artificial Intelligence - General,Computer Bks - General Information,Computer Books: General,Computers,General,Kernel functions,Machine Learning,Programming - General,Computers / Bioinformatics,Data capture & analysis,Pattern recognition
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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