Trial-and-error or K-fold cross-validation
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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.
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Greg Heath
le 1 Oct 2017
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
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