Omotayo-asiru asked . 2021-06-15

how to save and reuse a trained neural network

I just trained a neural network and i will like to test it with new data set that were not included in the training so as to check its performance on new data. This is my code; net = patternnet(30); net = train(net,x,t); save (net); y = net(x); perf = perform(net,t,y) classes = vec2ind(y); where x and t are my input and target respectively. I understand that save net; can be used but my questions are as follows ; 1.At what point in my code will i put save net 2.Using save net;, which location on the system is the trained network saved? 3.How can i load the trained network and supply new data that i want to test it with? Please Note: I want to be able to save the trained neural network such that when i run the code over and over again with the training data set,it gives same output. I have discovered that each time i run my code,it gives a different output which i do not want once i have an acceptable result. 

neural network , classification

Expert Answer

Prashant Kumar answered . 2024-12-21 15:14:20

1.At what point in my code will i put save net

 

 Any time after training it and before deleting it. 
However, give it a unique name so that it is not overwritten 
or used by mistake. 

 gregnet1 = net;
 save gregnet1
2.Using save net;, which location on the system is the trained network saved?
 
 
 What ever directory you are in when you save it UNLESS you 
specify another directory.

3.How can i load the trained network and supply new data that i want to test it with?

 load gregnet1
 newoutput = gregnet1(newinput);

Please Note: I want to be able to save the trained neural network such that when i run the code over and over again with the training data set,it gives same output. I have discovered that each time i run my code,it gives a different output which i do not want once i have an acceptable result.

 Then initialize the RNG to the same state before training to 
obtain reproducibility. See any of my training example posts.


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