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Neural Networks, K fold in patternnet

Asked by laplace laplace on 19 May 2013
This question is closed and may reopen in the future if edited.

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

3 Comments

Greg Heath on 19 May 2013

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 on 19 May 2013

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

laplace laplace

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