Using DEA-neural network approach to solve binary classification problems

In this paper we propose a new hybrid neural network include Data Envelopment Analysis (DEA) and Radial Basis Function Network (RBFN) for binary classification problem. In the supervised learning phase of neural network, the additive model is used to learn the classification function and Gaussian Radial Basis Function (GRBF) is used to the unsupervised learning phase of neural network. Compared with existing RBFN-DEA model for solving classification problems, the proposed model has low CPU time and moreover can be applied to solve classification problems with negative data.