Best Validation check number for MATLAB neural network
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I'm using 10-fold cross validation and patternent function for a binary classification problem in MATLAB. When I see neural network result window, in all trainings of neural network ( 80% training , 10% validation and 10% test with sample size 200~600 ) Early stopping is stopping my training process in iteration between 20~40. As you know the default value is maximum 6. What should i do about this problem? Should i increase maximum number of early stopping iteration checks?
Thanks.
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Accepted Answer
Greg Heath
on 5 Sep 2014
Edited: Greg Heath
on 5 Sep 2014
That is not necessarily a problem.
What error rates are you getting as you vary the number, H, of hidden nodes and sets of random initial weights?
I typically look at Ntrials = 10 different initial weight initializations for each candidate value of Hmin:dH:Hmax (numH~10).
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greg patternet Ntrials
Hope this helps.
Thank you for formally accepting my answer
Greg
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