Going from trainNetwork to trainnet

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psousa
psousa 2024-11-21
评论： psousa 2025-1-28
I've attached 3 files(see post below for latest version of these files):
  • trainNetworkEXAMPLE - my original trainNetwork implementation
  • trainnetEXAMPLE - the trainnet implementation
  • example.csv - data file with predictors and targets
The codes for the two examples are identical, the difference is only in the formatting of the input matrices.
trainNetworkEXAMPLE works as expected.
trainnetEXAMPLE works but convergence of the solver is different and solution is poor.
Both codes end with:
Training stopped: Met validation criterion
What am I getting wrong?
  2 个评论
Matt J
Matt J 2024-11-21
Seemingly nothing. Why do you think something is wrong?
psousa
psousa 2024-11-21
NMSE for training set and test set are considerably worse for version using trainnet.

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Sourabh
Sourabh 2025-1-28
编辑：Sourabh 2025-1-28
Hi @psousa
I too encountered the similar issue when using “trainnet” and “trainNetwork” method.
The workaround that worked in my case was to:
  1. Use @mse as the loss function instead of "mse" in “trainnet”.
[net,info] = trainnet(XTrain,TTrain,layers,@mse,options);
2. Set 'GradientThreshold' to ‘Inf’ in ‘trainingOptions’ of both the programs.
options = trainingOptions('adam',
...
'GradientThreshold',Inf,
...
);
Kindly refer to the below image:
  1 个评论
psousa
psousa 2025-1-28
Matlab support got back to me within a couple weeks and that was the solution they offered.
Thanks for looking into it.

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