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Is there any automatic code/way to choose/optimize the neural networks parameters on MATLAB?

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Dear experts,
I am an undergraduate student and i am doing my bachelor thesis in classification using neural networks.
I am struggling in optimizing neural networks hyper parameters (example: learning rate, regularization parameter, number of hidden neurons, mini-batch sizes, which training algorithm, weights/biases, mu(for Jacobin methods)....etc.). I read different books, where they provide some rules of thumb to choose the parameters.
However, my supervisor mentioned that there is an automatic way/code to choose the hyper parameters on matlab and then matlab runs with the parameters which fits the most and then it trains the data.
Is there any possibility to mention where can i find such an automated way or mention it in the answer? (i have looked everywhere in the Q&A asked about neural networks, and the documentation it is really hard to find such method so i decided to ask the experts themselves) Thanks in advance

Answers (3)

David Ding
David Ding on 26 May 2017
Hi Yehia,
Perhaps the following on model building and assessment might be of use to you:

Greg Heath
Greg Heath on 8 Nov 2017
Search the NEWSGROUP and ANSWERS with
greg patternnet
Most of my designs accept all defaults except
1. No of hidden nodes
2. Initial random weights
and use a double for loop to obtain tens of candidate designs that yield
mse(target-output) <= 0.01*mean(var(target,1))
The resulting classification error rates are usually very acceptable. In rare cases, I have to reduce 0.01 to 0.005 or lower.
Hope this helps.
Thank you for formally accepting my answer

Alan Weiss
Alan Weiss on 8 Nov 2017
In addition to Greg's comment (and he is the source of most wisdom on this matter), perhaps this example will show you the technique your advisor is referring to (requires Statistics and Machine Learning Toolbox).
Alan Weiss
MATLAB mathematical toolbox documentation


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