First, we convert the target class indices, Tc, to vectors, T.
Then we design a probabilistic neural network with NEWPNN.
We use a SPREAD value of 1 because that is a typical
distance between input vectors.

>> T = ind2vec(Tc);
>> spread = 1;
>> net = newpnn(P,T,spread);