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Linear and Nonlinear Classifiers of Data with Support Vector Machines and Generalized Support Vector Machines

  • Talat NazirEmail author
  • Xiaomin Qi
  • Sergei Silvestrov
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 179)

Abstract

The support vector machine for linear and nonlinear classification of data is 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.

Keywords

Linear and nonlinear classification Support vector machine Generalized support vector machine Kernel function 

Notes

Acknowledgements

Talat Nazir and Xiaomin Qi are grateful to the Erasmus Mundus project FUSION for supporting the research visit to Mälardalen University, Sweden, and to the Research environment MAM in Mathematics and Applied Mathematics, Division of Applied Mathematics, the School of Education, Culture and Communication of Mälardalen University for creating excellent research environment.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Division of Applied MathematicsSchool of Education, Culture and Communication, Mälardalen UniversityVästeråsSweden
  2. 2.Department of MathematicsCOMSATS Institute of Information TechnologyAbbottabadPakistan

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