Trial-and-error or K-fold cross-validation

Hello,

As researcher, i would like to ask for efficient algorithm to determine ANN's architecture (number of hidden neurons in one hidden layer),and i can not choose between Trial-and-Error and K-Fold Cross-validation. Indeed, most of researchers use in their articles K-Fold Cross-validation and i do not know why ? Thank you for you answer.

Answer 1

[Greg Heath]

If you search in both the NEWSGROUP and ANSWERS you will see zillions of examples of my two loop solution:

%Outer loop over number of hidden nodes, e.g.,

 rng(0), j=0
 for h = Hmin:dH:Hmax
     j = j + 1
     net = fitnet(h);
     etc ...

%Inner loop over Ntrials sets of random initial weights

     for i = 1:Ntrials
         net = configure(net,x,t);
         etc ...

Hope this helps.

Thank you for formally accepting my answer

Greg

[Hamza Ali]

Thank you Mr Greg. i will keep you informed of the results in order to discuss them.