Nonlinear Classifier Design Research Based on SVM and Genetic Algorithm

Abstract

This paper presents a support vector machine (SVM) model structure, the genetic algorithm parameters of the model portfolio optimization model, and used for non-linear pattern recognition, the method is not only effective for linear problems, nonlinear problems apply effective; the law simple and easy, better than the multi-segment linear classifier design methods and BP network algorithm returns the error. Examples show the efficiency of its recognition of 100%.

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Cite this paper

@inproceedings{Zeng2015NonlinearCD, title={Nonlinear Classifier Design Research Based on SVM and Genetic Algorithm}, author={Wenjuan Zeng and Haibo Gao}, year={2015} }