Twin support vector machines: models, extensions and applications

This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literat...

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Detalles Bibliográficos
Autores principales: Jayadeva, Khemchandani, Reshma, Chandra, Suresh
Lenguaje:eng
Publicado: Springer 2017
Materias:
Engineering
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-46186-1
http://cds.cern.ch/record/2240458
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author Jayadeva
Khemchandani, Reshma
Chandra, Suresh
author_facet Jayadeva
Khemchandani, Reshma
Chandra, Suresh
author_sort Jayadeva
collection CERN
description This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
publisher Springer
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spelling cern-22404582021-04-21T19:24:06Zdoi:10.1007/978-3-319-46186-1http://cds.cern.ch/record/2240458engJayadevaKhemchandani, ReshmaChandra, SureshTwin support vector machines: models, extensions and applicationsEngineeringThis book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.Springeroai:cds.cern.ch:22404582017
spellingShingle Engineering
Jayadeva
Khemchandani, Reshma
Chandra, Suresh
Twin support vector machines: models, extensions and applications
title Twin support vector machines: models, extensions and applications
title_full Twin support vector machines: models, extensions and applications
title_fullStr Twin support vector machines: models, extensions and applications
title_full_unstemmed Twin support vector machines: models, extensions and applications
title_short Twin support vector machines: models, extensions and applications
title_sort twin support vector machines: models, extensions and applications
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-46186-1
http://cds.cern.ch/record/2240458
work_keys_str_mv AT jayadeva twinsupportvectormachinesmodelsextensionsandapplications
AT khemchandanireshma twinsupportvectormachinesmodelsextensionsandapplications
AT chandrasuresh twinsupportvectormachinesmodelsextensionsandapplications

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