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Support vector machines: optimization based theory, algorithms, and extensions

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs...

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Detalles Bibliográficos
Autores principales: Deng, Naiyang, Tian, Yingjie, Zhang, Chunhua
Lenguaje:eng
Publicado: Taylor and Francis 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/1618543
Descripción
Sumario:Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twi