Abstract
At present, the classification method based on nonlinear integral has been widely used. In this paper, Choquet integral value is used as a nonlinear integral discriminant, and a new discriminant classification model is proposed. The classification model maps the data sets which cannot be linearly separable in low dimensional space into high-dimensional space by nonlinear integral discriminant, and then classifies them by Choquet integral. Because there are too many parameters of classification model in the process of classification, particle swarm optimization is used to optimize the parameters, and then combined with the idea of support vector machine to classify the model. Finally, through the MATLAB programming experiment, the classification model proposed in this paper is compared with the SVM classification model, and the experimental results show the feasibility and effectiveness of the model.
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