An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. John Shawe-Taylor, Nello Cristianini
An-Introduction-to-Support.pdf
ISBN: 9780521780193 | 189 pages | 5 Mb
- An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
- John Shawe-Taylor, Nello Cristianini
- Page: 189
- Format: pdf, ePub, fb2, mobi
- ISBN: 9780521780193
- Publisher: Cambridge University Press
Pdf books downloads An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (English literature) 9780521780193
<p>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. </p>
Support Vector Machines - Fico
Christianini, Nello and Shawe-Taylor, John (2000), An Introduction to Support Vector Learning Machines and other kernel-based learning methods, Cambridge
An introduction to kernel-based learning algorithms - Center for Data
Index Terms—Boosting, Fisher's discriminant, kernel methods, kernel PCA learning machines, e.g., support vector machines (SVMs). [1]–[6], kernel Fisher the parameters in SVMs and other kernel-based approaches. Fi- nally, we describe
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