How to customize performance function in MATLAB neural network.

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Chibuzo Nnonyelu
Chibuzo Nnonyelu 2015 年 4 月 22 日
コメント済み: Chibuzo Nnonyelu 2018 年 1 月 14 日
Greetings. I am relatively a beginner in neural network. I started off using MATLAB neural network tool until I was met with some limitations. My problem is as follows: 1.) I would like to be able to customize my performance function such that I don't use the inbuilt performance functions such as mse, mae, etc. 2.) I would also like to be able to modify how many training iteration before any validation. I read somewhere that it takes five (5) training iteration before every consecutive validation check. However, if someone has an idea of a better neural network tool that is good for function approximation using MLP, please recommend.
Thank you.

回答 (1 件)

Greg Heath
Greg Heath 2015 年 4 月 22 日
1. Start with a copy of mse (or other performance function)
a. Enter the command: type mse
b. Copy and save the result under a different name, e.g., myperf
c. Modify it
d. Save it
e. Change the net property
net.perfornFcn = myperf;
f. Test it.
2. net.trainParam.max_fail = 10; %(or whatever)
3. Enter WITHOUT THE SEMICOLON!
net = fitnet
You will see a long list of default parameters that can be changed to your liking.
Hope this helps.
Thank you for formally accepting my answer
Greg
PS: This is explained in the website documentation section on custom functions.
  3 件のコメント
Arygianni Valentino
Arygianni Valentino 2017 年 12 月 1 日
Hi Greg..
If you do not mind, would you explain more and give an example of the step Modify the performance function? Since I got stuck there. I could not find the formula where the corresponding performance function does the calculation.
Chibuzo Nnonyelu
Chibuzo Nnonyelu 2018 年 1 月 14 日
This approach did not actually work. I ended up writing my own MLP BP from scratch using C#. C# ensured faster training with larger data. And I was able to try my custom error and performance function.
Using MATLAB for ANN is only good if you are just fine with its available functions and all.

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