Newman23 asked . 2021-06-17

How to get validation test and training errors of a neural network?

I have created and trained a neural network using the following code .I want to know how to get the training testing and validation errors/mis-classifications the way we get using the matlab GUI.

trainFcn = 'trainscg';  % Scaled conjugate gradient backpropagation.

   % Create a Pattern Recognition Network
   hiddenLayerSize = 25;
   net = patternnet(hiddenLayerSize);

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = trainper/100;
net.divideParam.valRatio = valper/100;
net.divideParam.testRatio = testper/100; 

% Train the Network
[net,tr] = train(net,x,t);

neural network , neural networks , matlab , deep learning , simulink

Expert Answer

John Williams answered . 2024-12-21 19:35:23

BOTH documentation commands

 help patternnet
and
 doc patternnet

have the following sample code for CLASSIFICATION & PATTERN-RECOGNITION:

    [x,t] = iris_dataset;
     net  = patternnet(10);
     net  = train(net,x,t);
     view(net)
     y = net(x);
     perf = perform(net,t,y);
     classes = vec2ind(y);

However, the following are missing

 1. Dimensions of x and t 
 2. Plots of x, t, and t vs x
 3. Minimum possible number of hidden nodes
 4. Initial state of the RNG (Needed for duplication)
 5. Training record, tr
 6. Plots of e = y-t vs x
 7. Misclassified cases
 8. trn/val/tst Error rates

For details see my NEWSGROUP posts

 SIZES OF MATLAB CLASSIFICATION EXAMPLE DATA SETS
http://www.mathworks.com/matlabcentral/newsreader/...
       view_thread/339984

 and

 BEYOND THE HELP/DOC DOCUMENTATION : PATTERNNET for 
 NN Classification and PatternRecognition
 http://www.mathworks.com/matlabcentral/newsreader/...
     view_thread/344832

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