This class implements either a:
Probabilistic Neural Network (PNN)
General Regression Neural Network (GRNN)
To use a PNN specify an output mode of classification, to make use of a GRNN
specify either an output mode of regression or un-supervised autoassociation.
Create a bubble neighborhood function that will return 1.0 (full update)
for any neuron that is plus or minus the width distance from the winning
neuron.
A radial basis function (RBF) network uses several radial basis functions to
provide a more dynamic hidden layer activation function than many other types
of neural network.
Set the number of output neurons, should not be used with a hopfield
neural network, because the number of input neurons defines the number of
output neurons.