training progress graph of 'trainNetwork'

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Deepak Sivadas
Deepak Sivadas on 1 Feb 2019
Edited: kh rezaee on 15 Apr 2022
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

Answers (4)

Areej Varamban Kallan
Areej Varamban Kallan on 8 Feb 2019
Hi Deepak,
Please try the following:
  1. After the training is complete, close all the figures except the training plot.
  2. Execute the following commands on MATLAB command line:
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.
  9 Comments
kh rezaee
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.

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avi.loey
avi.loey on 31 Jul 2019
Thankyou. This was exactly what I needed. Works perfectely !!!!

Amit DOegar
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
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?

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Xiao Liu
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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