I noticed that performances in the training record of a neural network are always consistently different from perfomances calculated manually. It looks like the numbers in training record are not calculated directly with the performance function of the net. Here's some code:
First, I train a neural network
x = (0:0.1:10);
t = sin(x);
net = fitnet(6);
[net,trainingrecord] = train(net,x,t);
y = net(x);
then I manually calculate the performance of the net on the test sample
for i = 1:size(trainingrecord.testInd,2)
test_y(i) = y(1,trainingrecord.testInd(i));
test_t(i) = t(1,trainingrecord.testInd(i));
end;
manualperf = 0;
for i = 1:size(trainingrecord.testInd,2)
manualperf = manualperf + (test_y(i)-test_t(i))^2;
end;
manualperf = manualperf/size(trainingrecord.testInd,2);
This is the same performance, calculated by perform function and they are exactly the same:
autoperf = perform(net,test_y,test_t);
isequal(autoperf,manualperf)
ans =
1
But they both differ from trainingrecord.best_tperf
>> autoperf
autoperf =
1.129785002584019e-06
>> manualperf
manualperf =
1.129785002584019e-06
>> tr.best_tperf
ans =
1.129785002584038e-06
>> isequal(autoperf,manualperf,trainingrecord.best_tperf)
ans =
0
It looks like the performance in the training record is not calculated straightfowardly by calling the perform function or maybe there is some kind of error accumulated through the code. Any ideas?
