The Training of Radial Basis Function Network Classifier with Cooperative Clustering

The selection of centers and widths parameter has a strong influence on the performance of radial basis function neural network. In this paper, we present a novel approach of clustering, which we called cooperative clustering, and use it for selection of centers of radial basis function neural network. The experimental results are given to show that the approach could not only effectively improve the training speed, but also keep classification accuracies.