Problem formulations and solvers in linear SVM: a review

Support vector machine (SVM) is an optimal margin based classification technique in machine learning. SVM is a binary linear classifier which has been extended to non-linear data using Kernels and multi-class data using various techniques like one-versus-one, one-versus-rest, Crammer Singer SVM, Wes...

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Veröffentlicht in:	The Artificial intelligence review Jg. 52; H. 2; S. 803 - 855
Hauptverfasser:	Chauhan, Vinod Kumar, Dahiya, Kalpana, Sharma, Anuj
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.08.2019 Springer Springer Nature B.V
Schlagworte:	Artificial Intelligence Big Data Classification Classifiers Computer Science Data management Formulations Kernel functions Machine learning Solvers Support vector machines Word sense disambiguation Support vector machines Support vector classification Linear SVM SVM solvers Optimization problem
ISSN:	0269-2821, 1573-7462
Online-Zugang:	Volltext
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