How to differentiate between Mse(training) and Mse(testing) ??
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Hello, i would like to know how to differentiate between Mse(training) and Mse(testing) during training phases this is my part of my ANN's code :
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 20/100;
net.divideParam.testRatio = 10/100;
net.performFcn = 'mse'
MSEt(j,H) = mse(net,targets,outputs);%mean square error
*my question is that MSE calculated is for training error or for testing error ??
Help please*
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Accepted Answer
Greg Heath
on 23 Sep 2016
In order to obtain the break down of mse into its trn/val/tst parts you have to obtain the training record, tr from training;
[ net tr Y E Xf Af ] = train ( net, X ,T, Xi, Ai );
help train
doc train
Hope this helps.
Greg
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