Learning with Support Vector Machines

Language: English

Published by Springer International Publishing AG, CH, 2011

3031004248 / 9783031004247

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Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such as prediction with real-valued outputs, novelty detection and the handling of complex output structures such as parse trees. Finally, we give an overview of the main types of kernels which are used in practice and how to learn and make predictions from multiple types of input data. Table of Contents: Support Vector Machines for Classification / Kernel-based Models / Learning with Kernels.

Seller Inventory # LU-9783031004247

Title
Learning with Support Vector Machines
Author
Colin Campbell, Yiming Ying
Publisher
Springer International Publishing AG, CH
Publication year
2011
Condition
New
Binding
Paperback
Language
English
ISBN 10
3031004248
ISBN 13
9783031004247

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