Increasing the number of epochs to reach the performance goal
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Hello,
I am training the neural network with input vector of 85*650 and target vector of 26*650. Here is the list of parameters that I have used
net.trainParam.max_fail = 6;
net.trainParam.min_grad=1e-5;
net.trainParam.show=10;
net.trainParam.lr=0.9;
net.trainParam.epochs=13500;
net.trainParam.goal=0.001;
Number of hidden nodes=76
As you can see ,I have set the number of epochs to 13500. Is it OK to set the number of epochs to such a large number?. Performance goal is not reaching if the number of epochs is decreased and I am getting a bad classification while testing.
1 Comment
An Hoang
on 8 Oct 2017
I thought your epochs is so big and too much training is actually bad because the network overfits to the training data, and then performs badly against new data that it hasn't never seen it before.
Accepted Answer
Greg Heath
on 22 Apr 2014
Edited: Greg Heath
on 2 May 2014
[ I N ] = size(input) % [ 85 130 ]
[ O N ] = size(output) % [ 26 130 ]
Ntrn = N - 2*round(0.15*N)% 90
Ntrneq = Ntrn*O % 2340 training equations
%Nw = (I+1)*H+(H_1)*O % unknown weights
% Ntrneq >> Nw, or equivalently, H << Hub where
Hub = -1+ceil((Ntrneq-O) / (I+O+1)) % 20
Try to minimize I and H while using as many defaults as possible.
I don't remember ever having to incease the default numepochs.
Greg
3 Comments
Greg Heath
on 23 Apr 2014
MY APPROACH IS TO VARY NUMBER OF HIDDEN NODES AND TO DESIGN ~ NTRIALS = 10 NETS FOR EACH CANDIDATE VALUE OF H.
I use as many defaults as possible. Rarely have I considered increasing the maximum number of epochs.
MD Towhid Ur Rahman
on 15 Apr 2022
I like the equations you mentioned here, my question is -"Is there an established paper/ referencce/book that is published by any other author or yourself that metions these equations?" Thanks in advance! If yes, the would you mind sharing the resource with me [Please don't attach links, I just need the Title and Author, I can find it myself]
More Answers (1)
Greg Heath
on 23 Apr 2014
One problem you have is that you are specifying the mse and mingrad goals without considering the scale of the target. I find that reasonable goals are
MSEgoal = 0.01*mean(var(ttrn',1))
MinGrad = MSEgoal/ 200
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