Free ebook download txt format An Introduction to Support Vector Machines and Other Kernel-based Learning Methods 9780521780193 iBook PDF

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. John Shawe-Taylor, Nello Cristianini

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

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ISBN: 9780521780193 | 189 pages | 5 Mb

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  • 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

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

Free ebook download txt format An Introduction to Support Vector Machines and Other Kernel-based Learning Methods 9780521780193 iBook PDF

<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>

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techniques and is comparable to that of other SVM-based methods In 1999, Tommi Jaakkola, Mark Diekhans and David Haussler introduced a new from the area of machine learning, known as a support vector machine (SVM). In.
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Support vector machines (SVMs) are a set of related supervised learning methods that analyze data and recognize whether a new example falls into one category or the other. New examples are then mapped into that same space and predicted to belong to a category based on which side of 
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