Query on Neural network results

I am working on handwritten character recognition. I have trained the neural network with (130 * 85) inputs and (130 *26) targets. I am using the nprtool in matlab and here are the results which I am getting with 50 hidden neurons

Training : 0 % error validation : 0% error Testing : 5 % error

But, I am getting these results after lot of retraining. So will I be able to classify the characters with these results?

Answer 1

[Greg Heath]

 I = 85, O = 26, N = 130, H = 50

 [ I N ] = size(input)   % [ 85 130]

 [ O N ] = size(target)  % [ 26 130]

 Ntrn  = N -2*(0.15*N)   % 91 training examples

 Ntrneq= Ntrn*O          % 2366 training equations

 Nw    = (I+1)*H+(H+1)*O % 5626 unknown weights

% Ntrneq >> Nw == H << Hub

 Hub = -1 + ceil( (Ntrneq-O) / ( I + O + 1 ) % 20

Try to lower H as much as possible. It should make your model more robust (w.r.t. noise, measurement error and unseen data). Typically, I try to look at ~10 different values for H and ~Ntrials = 10 different designs for each value of H to mitigate the probability of getting a poor set of initial weights.

I have many posts in the NEWSGROUP and ANSWERS. Search on

 greg patternnet Ntrials
 greg newpr      Ntrials

 for h = Hmin:dH:Hmax
 ....
     for i = 1:Ntrials
 ....
     end
 end

Hope this helps,

Greg