How detect by code which condition halted NN traning
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I'm using a feedforwardnet NN and I would like to know from code which condition determined NN training stop (max validation checks reached, max epoch, performance goal, etc..). Is it possible? Thanks for your replys. Regards.
Sergio
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Accepted Answer
Greg Heath
on 27 Jun 2014
>>
[x,t] = simplefit_dataset;
net = fitnet(10);
[net tr] = train(net,x,t);
stopcriteria = tr.stop
tr = tr
stopcriteria =
Validation stop.
tr =
trainFcn: 'trainlm'
trainParam: [1x1 struct]
performFcn: 'mse'
performParam: [1x1 struct]
derivFcn: 'defaultderiv'
divideFcn: 'dividerand'
divideMode: 'sample'
divideParam: [1x1 struct]
trainInd: [1x66 double]
valInd: [1x14 double]
testInd: [1x14 double]
stop: 'Validation stop.'
num_epochs: 16
trainMask: {[1x94 double]}
valMask: {[1x94 double]}
testMask: {[1x94 double]}
best_epoch: 10
goal: 0
states: {1x8 cell}
epoch: [1x17 double]
time: [1x17 double]
perf: [1x17 double]
vperf: [1x17 double]
tperf: [1x17 double]
mu: [1x17 double]
gradient: [1x17 double]
val_fail: [1x17 double]
best_perf: 1.3525e-04
best_vperf: 1.7348e-04
best_tperf: 5.9455e-04
Hope this helps.
Thank you for formally accepting my answer
Greg
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