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A novel binary data classification algorithm based on the modified reaction-diffusion predator-prey system with
Jialin Chen1, Xinlei Chen2, Jian Wang1,3,4
1School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Abstract:
In this study, we propose a modified reaction-diffusion prey-predator model with a Holling-II function for binary data classification. In the model, we use u and v to represent the densities of prey and predators, respectively. We modify the original equation by substituting the term v with f-v to obtain a stable and clear nonlinear decision surface. By employing a finite difference method for numerical solution of the original model, we conduct various experiments in two-dimensional and three-dimensional spaces to validate the feasibility of the classifier. Additionally, with consideration for wide real applications, we perform classification experiments on electroencephalogram signals, demonstrating the effectiveness and robustness of the classifier in binary data classification.
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