Classification error at each epoch

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alessandro
alessandro am 19 Jan. 2016
Beantwortet: Greg Heath am 22 Jan. 2016
Hi there, I am performing a classification problem using Neural Network tool. I did the following:
hiddenLayerSize = 10;
net = patternnet(hiddenLayerSize);
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
net.divideParam.trainRatio = 70/100; net.divideParam.valRatio = 15/100; net.divideParam.testRatio = 15/100;
net.trainFcn = 'trainscg'; % Scaled conjugate gradient
net.performFcn = 'mse'; % Mean squared error
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ... 'plotregression', 'plotfit'};
I then trained the network
[net,tr] = train(net,inputs,targets);
and got some results. From tr information, I can extract classification hit/miss for each class, as well as mse at each epoch. However, is it possible to extract, at each epoch, percentage of hit/miss for each sub-class?
How mse is estimated at each time step?
Is hit/miss percentage for each class explicitly computed at each time step?
Best Regards, Alessandro

Akzeptierte Antwort

Greg Heath
Greg Heath am 22 Jan. 2016
Classification error at each epoch Asked by alessandro on 19 Jan 2016 at 8:45 Latest activity Edited by alessandro on 19 Jan 2016 at 8:45 Hi there, I am performing a classification problem using Neural Network tool. I did the following:
GEH1 = 'I deleted default statements'
net = patternnet;
net.performFcn = 'mse'; % Mean squared error
..[net,tr] = train(net,inputs,targets);
and got some results. From tr information, I can extract classification hit/miss for each class, as well as mse at each epoch. However, is it possible to extract, at each epoch, percentage of hit/miss for each sub-class?
GEH2 ='YES. The locations of the trn/val/tst subclass indices are in tr'
How mse is estimated at each time step?
GEH3 = 'Isn't it obvious?'
Is hit/miss percentage for each class explicitly computed at each time step?
GEH4 = ' No'
Hope this helps
Thank you for formally accepting my answer
Greg

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