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This paper presents a linear programming formulation for linear and nonlinear piecewise multi-classification support vector machines model for multi-category discrimination of sets or objects. The proposed model can be used to generate linear and nonlinear piecewise classifiers depending on the kernel function employed. Advantages of the linear programming multi-classification SVM formulation include...
This paper presents Tikhonov regularization based classification models for binary discrimination of sets or objects. The proposed models include a linear classification, nonlinear kernel classification and a reduced kernel classification model in the case of large scale problems. For the reduced kernel formulation, the dimension reduction of the kernel matrix is achieved by selecting random subsets...
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