A supervised fuzzy clustering for Radial Basis Function Neural Networks training

In this paper we present a new learning algorithm for radial basis function neural networks (RBFNN's) based on a supervised fuzzy clustering technique. Our methodology follows the conditional fuzzy clustering presented by W. Pedrycz (1998) and permits to obtain a completely automatic clustering, where data agglomeration is based on both input and output pattern values.