Fuzzy Probabilistic Neural Networks: A practical approach to the implementation of Baysian classifier

A classifier with the optimum decision, Baysian classifier could be implemented with Probabilistic Neural Networks (PNNs). The authors presented a new competitive learning algorithm for training such a network when all classes are completely separated. This paper generalizes our previous work to the case of overlapping categories. In our new perspective, the network is, in fact, made blind with respect to the overlapping training samples using fuzzy concepts, so the new training algorithm is called Fuzzy PNN (or FPNN). The usefulness of FPNN has been proved by some classification problems. The simulation results highlight the merit of the proposed method.