The probabilistic neural network PNN represents an interesting parallel implementation of Bayes strategy for pattern classification. Its training phase consists in generating a new neuron for each training pattern, whose weights equal the pattern components. This noniterative training procedure is extremly fast, but leads to a very high number of neurons in those cases in which large data sets are avilable.