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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 th...

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Detalles Bibliográficos
Autores principales: Campbell, Colin, Ying, Yiming
Lenguaje:eng
Publicado: Morgan & Claypool Publishers 2010
Materias:
Acceso en línea:http://cds.cern.ch/record/1486593
Descripción
Sumario: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 a