Analysis of the Performance of Ensemble of Perceptrons

In this study we analyze the performance of an ensemble model composed of several perceptrons that can effectively deal with nonlinear classification problems. Although each member of the ensemble can only deal with linear classification problems, through a competitive training mechanism, the ensemble is able to automatically allocate a part of the learning space that is linearly separable to each member, thus decomposing non-linear classification problems into several more manageable linear problems. In this paper, we gave the performance analysis of the ensemble with regard to some benchmark problems.