Linear and Nonlinear Classifiers of Data with Support Vector Machines and Generalized Support Vector Machines
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.
KeywordsLinear and nonlinear classification Support vector machine Generalized support vector machine Kernel function
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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