How to analyse the results of training of neural network

Hi, i tried to create neural network for classification using nprtool and i tried to modify the code but i couldn't analyse the results and what should i do with this results .So Can anyone please tell me because i have no idea ? This is my code :

 x = patientInputs;
t = patientTargets;
 N=1012
 I=9
 O=2
[ I N ] = size(x) 
 [ O N ] = size(t) 
 Ntrn   = N-2*round(0.15*N)  % 708
 Ntrneq = Ntrn*O        %1416    
    %For a robust design desire Ntrneq >> Nw or
   H=10
    Hub = -1+ceil( (Ntrneq-O) / (I+O+1)) %   Hub =117
    Nw = (I+1)*H+(H+1)*O       % Number of unknown weights = 122
   %H << Hub = -1+ceil( (Ntrneq-O) / (I+O+1)) 
 Ntrials = 10
 rng(0)
 j=0
 for h =round([Hub/10, Hub/2, Hub])
    j  = j+1
    h  = h   %12
    Nw            = (I+1)*h+(h+1)*O  % 146 
    Ndof          = Ntrneq-Nw       %1270
    net           = patternnet(h);
    net.divideFcn = 'dividerand';           % 'dividetrain'
    for i = 1:Ntrials
        net                          = configure(net,x,t);
        [ net tr outputs regerrors ] = train(net,x,t);
        assignedclasses              = vec2ind(outputs);
        trueclasses = vec2ind(t);
        classerr                     = assignedclasses~=trueclasses;
        Nerr(i,j)                    = sum(classerr);
        % FrErr                      = Fraction of Errors (Nerr/N) 
        [FrErr(i,j),CM,IND,ROC]  = confusion(t,outputs);
        FN(i,j) = mean(ROC(:,1));    % Fraction of False Negatives
        TN(i,j) = mean(ROC(:,2)) ;   % Fraction of True Negatives
        TP(i,j) = mean(ROC(:,3));    % Fraction of True Positives
    end
 end
 PctErr=100*Nerr/N

And this are the resultas that i got :

Ntrn =

   708

Ntrneq =

        1416

H =

    10

Hub =

   117

Nw =

   122

Ntrials =

    10

j =

     0

j =

     1

h =

    12

Nw =

   146

Ndof =

        1270

j =

     2

h =

    59

Nw =

   710

Ndof =

   706

j =

     3

h =

   117

Nw =

        1406

Ndof =

    10

PctErr =

   41.2055   37.5494   34.0909
   46.3439   42.8854   43.0830
   38.9328   35.8696   37.2530
   41.4032   35.3755   37.5494
   37.6482   42.5889   34.4862
   41.6008   40.5138   32.8063
   38.2411   41.6008   33.9921
   38.0435   34.7826   37.0553
   39.1304   37.0553   38.5375
   38.0435   34.8814   35.5731

Answer 1

[Greg Heath]

It is considered ill-mannered to post the same problem in both

 NEWSGROUP and ANSWERS

See my answer in the NEWSGROUP

Greg