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portada Learning with Support Vector Machines
Type
Physical Book
Author
Publisher
Language
English
Pages
83
Format
Paperback
Dimensions
23.5 x 19.1 x 0.5 cm
Weight
0.18 kg.
ISBN13
9783031004247
Categories

Learning with Support Vector Machines

Colin Campbell (Author) · Yiming Ying (Author) · Springer · Paperback

Learning with Support Vector Machines - Campbell, Colin ; Ying, Yiming

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Synopsis "Learning with Support Vector Machines"

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

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