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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 2691 training rounds!

End result


Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.99926038831172, 0.004327980616112, 0.00038551154498149, 0.0061985285514348)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.99924011426832, -0.0057561660247348, -0.0039105526031867, 0.0016810564272154)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (-0.0019293765672378, 0.99722791058837, 0.0046496853127109, -0.0032951558394117)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (-0.002410115727953, 0.9972453829954, -0.00095724626244107, -0.0034432964528781)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (-0.004851551533261, -0.0072005718503968, 0.99986835512612, 0.00036575977443606)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (9.0682853486018E-5, 0.0068358349547702, 0.99885500731494, 0.0083361257532628)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (-0.0086576519863145, -0.0067682627000503, 0.0031813315250632, 0.99914701342275)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (-0.0086367568165331, -0.0064530358785949, 0.001797485819491, 0.9991477158004)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (0.016285626455758, -0.00069636691393796, -0.0015767462565764, 0.99920493635853)
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