Going from trainNetwork to trainnet

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

Seemingly nothing. Why do you think something is wrong?
NMSE for training set and test set are considerably worse for version using trainnet.

请先登录,再进行评论。

 采纳的回答

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

Matlab support got back to me within a couple weeks and that was the solution they offered.
Thanks for looking into it.

请先登录,再进行评论。

更多回答(0 个)

类别

帮助中心File Exchange 中查找有关 Deep Learning Toolbox 的更多信息

产品

版本

R2024b

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by