A deterministic method for establishing the initial conditions in the RCE algorithm

The RCE algorithm, which can be considered as belonging to the category of the Region of Influence (ROI) incremental algorithms, is one of the first and most widely used incremental algorithms. It is well known that the performance of this algorithm is limited by constraints affecting the initial parameter settings: order in which input patterns are presented during the training phase and initial radius to be used for the generated hyperspheres. In this paper, we propose a deterministic method for obtaining automatically the suitable initial radius for a given input problem. The method is based on the definition of several functions which give a quantitative measure of the geometrical relations between the different categories defined in the input space. As the simulation results show, this method improves significantly the performance (in terms of number of units generated and generalization capability) of the RCE algorithm.