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input=(
(0,1,0,0,0,1,0,0),
(0,1,0,0,0,1,1,0),
(1,0,1,1,0,0,0,1),
(0,0,1,1,0,0,0,1),
(1,0,0,0,0,1,1,0),
(1,1,0,0,0,1,1,0),
(1,1,1,1,1,1,1,0),
(1,1,1,0,1,1,1,1),
(1,0,1,1,1,1,1,1)
);
output=(
(1,0,0,0),
(1,0,0,0),
(0,1,0,0),
(0,1,0,0),
(0,0,1,0),
(0,0,1,0),
(0,0,0,1),
(0,0,0,1),
(0,0,0,1)
);
max=5
epoch=10000
error=0.01
Success in 5391 training rounds!

End result


Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.9980216867005, -0.00020621061239245, 0.0049854578935096, -0.00036691374529427)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.99832705441762, 0.0030732038374001, 0.0020991526109288, 0.00030630477203405)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (0.00056537195850154, 0.99826039580517, 0.0038744918137558, 0.00060240232977072)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (0.00073372446703807, 0.99957462623778, -0.0078439404618277, -0.0028250900698058)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (-0.0018131590598054, -0.0057877231583878, 0.99824528942708, -0.00027013808700165)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (-0.0076212464759863, 0.010522161437371, 0.9978221178978, -0.003131680213074)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (0.002852133610958, 0.00063106661693038, -8.6765732949061E-5, 0.99945320753713)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (0.0078726173475452, -0.0040172307387878, -0.00042060220866935, 0.99946936847801)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (-0.01876819513656, 0.0041762131987881, -0.0025060164318309, 0.99948310684825)
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