Neural Networks, K fold in patternnet

i got 3x1 matrices that i wanna classify in to two groups using k fold crossvalidation method.

1. i have to train a network with the patternnet algorithm
2. and apply to the data the k-fold cross validation method,

Indices = crossvalind('Kfold',inputs , 5);
    for i=1:5
         test = (Indices == i); 
         train = ~test;
     for n = 1:5  
               net = patternnet(inputs,targets,h);    %test train
               net.divideFcn = 'dividetrain';
               net.trainParam.goal = MSEgoal;
               net.trainParam.min_grad = MinGrad;
               [net,tr] = train(net,inputs,targets);   % test train
                bestepoch = tr.best_epoch;
                R2(n,h) = 1 - tr.perf(bestepoch)/MSEtrn00;
           end

the above code is really wrong can someone correct it? its urgent

[Greg Heath]

This code is not even close to being correct.

Take some time to think it through, revise, add clarifying comments and either run on one of the nndatasets or include your data and accompanying error messages.

[laplace laplace]

i know it is.. i just cant think smth else.. its really really urgent if you find some time i would appreciate it..

[Walter Roberson]

http://www.mathworks.com/matlabcentral/answers/29922-why-your-question-is-not-urgent-or-an-emergency