- After the training is complete, close all the figures except the training plot.
- Execute the following commands on MATLAB command line:
training progress graph of 'trainNetwork'
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Hi,
I am using trainNetwork function in deep neural network toolbox.
A graph appears automatically appears showing training progress. I like to know how can the plot styles (say, color, label size) be modified by user?
Also it is of interest to save the plot for future reference. But unlike matlab figure window, it doesnot allow that also.
Pls inform me on how to access and modify settings in training progress graph.
Thanks,
Deepak
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Answers (4)
Areej Varamban Kallan
on 8 Feb 2019
Hi Deepak,
Please try the following:
h= findall(groot,'Type','Figure');
h.MenuBar = 'figure';
The training plot will now have a menu bar.
3. Click Edit-> Figure Properties. This will open the Poperty Editor window.
4. Use the options in the Property Editor window to change plot styles.
5. Similary, you can save the figure from 'File->Save'
To hide the menu bar, execute the following command on MATLAB command line:
h.MenuBar = 'none';
I hope this helps.
10 Comments
kh rezaee
on 15 Apr 2022
Edited: kh rezaee
on 15 Apr 2022
I appreciate your response, Areej Varamban Kallan. In the 2020 version, I was able to edit the output after I used your command for training progress figure. However, I am unable to edit the figure in version 2022, and I receive the following error message. Is there a way to make the menu appear?
Functionality not supported with figures created with the uifigure function.
Qiaohui He
on 5 Jul 2022
Maybe u can try
[net tr] = trainNetwork(XTrain,YTrain,layers,options);
save(tr)
and the 'tr'will store the data of the training process. Then the data in workspace of tr.mat could be applied to use plot function.
Amit DOegar
on 18 Jun 2020
h= findall(groot,'Type','Figure');
h.MenuBar = 'figure';
How to do this for multiple open figures as in k-fold we need to save all plots
or how to get handle of all open figures in matlab
1 Comment
krishna Chauhan
on 19 Jul 2020
Hey Amit
How are you able to see what cross validation its training?
I mean where to assign cross k validation in trainNetwork?
Xiao Liu
on 18 Jul 2021
you can use the data from working space and plot one more picture for yourself.
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