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Linear and Nonlinear Classifiers of Data withSupport Vector Machines and GeneralizedSupport Vector Machines
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Department of Mathematics, COMSATS Institute of Information Technology. (MAM)ORCID iD: 0000-0001-6516-3212
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0002-0865-7248
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0003-4554-6528
2016 (English)In: Engineering Mathematics II: Algebraic, Stochastic and Analysis Structures for Networks, Data Classification and Optimization / [ed] Sergei Silvestrov; Milica Rancic, Springer, 2016, 377-396 p.Chapter in book (Refereed)
Abstract [en]

The support vector machine for linear and nonlinear classification of datais studied. The notion of generalized support vector machine for data classifications is used. The problem of generalized support vector machine is shown to be equivalent to the problem of generalized variational inequality and various results for the existence of solutions are established. Moreover, examples supporting the results are provided.

Place, publisher, year, edition, pages
Springer, 2016. 377-396 p.
Series
Springer Proceedings in Mathematics and Statistics, ISSN 2194-1009 ; 179
Keyword [en]
generalized support vector machine, data classification, generalized variational inequality
National Category
Computational Mathematics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-33385DOI: 10.1007/978-3-319-42105-6Scopus ID: 2-s2.0-85012915546ISBN: 978-3-319-42104-9 (print)ISBN: 978-3-319-42105-6 (print)OAI: oai:DiVA.org:mdh-33385DiVA: diva2:1034029
Available from: 2016-10-11 Created: 2016-10-11 Last updated: 2017-03-02Bibliographically approved
In thesis
1. Fixed points, fractals, iterated function systems and generalized support vector machines
Open this publication in new window or tab >>Fixed points, fractals, iterated function systems and generalized support vector machines
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis, fixed point theory is used to construct a fractal type sets and to solve data classification problem. Fixed point method, which is a beautiful mixture of analysis, topology, and geometry has been revealed as a very powerful and important tool in the study of nonlinear phenomena. The existence of fixed points is therefore of paramount importance in several areas of mathematics and other sciences. In particular, fixed points techniques have been applied in such diverse fields as biology, chemistry, economics, engineering, game theory and physics. In Chapter 2 of this thesis it is demonstrated how to define and construct a fractal type sets with the help of iterations of a finite family of generalized F-contraction mappings, a class of mappings more general than contraction mappings, defined in the context of b-metric space. This leads to a variety of results for iterated function system satisfying a different set of contractive conditions. The results unify, generalize and extend various results in the existing literature. In Chapter 3, the theory of support vector machine for linear and nonlinear classification of data and the notion of generalized support vector machine is considered. In the thesis it is also shown that the problem of generalized support vector machine can be considered in the framework of generalized variation inequalities and results on the existence of solutions are established.

Place, publisher, year, edition, pages
Västerås: Mälardalen University Press, 2016. 66 p.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 247
Keyword
support vector machine, fixed points, iterated function system, variational inequality
National Category
Computational Mathematics
Research subject
Mathematics/Applied Mathematics
Identifiers
urn:nbn:se:mdh:diva-33511 (URN)978-91-7485-302-5 (ISBN)
Presentation
2016-12-12, U2-016, Mälardalen University, Västerås, 14:15 (English)
Opponent
Supervisors
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FUSION
Available from: 2016-11-09 Created: 2016-11-08 Last updated: 2016-11-24Bibliographically approved

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Publisher's full textScopushttp://www.springer.com/gp/book/9783319421049

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CiteExportLink to record
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Citation style
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