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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

End result


Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.99413073847226, -0.0039020728598959, 0.0032228814324112, -0.0014333261163599)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.99365704149475, 0.0021861750516721, 0.0016692041586029, -0.00099681619781349)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (-0.019768015543068, 0.99984236438695, -0.0018764751130177, -0.00090863741814113)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (0.022201977409513, 0.99970232774425, 0.0038065005479157, 0.00061221854916431)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (0.047804032672453, -0.0082413088759812, 0.9972409176126, -0.011795037176667)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (0.065657941777107, -0.016555314163255, 0.99720036774215, -0.012505540030668)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (0.0022197863320893, -0.00038354937263858, 0.00092512350822639, 0.99974133624913)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (0.0024861297005042, -0.00020129338959938, 0.00067266832423918, 0.99974066704642)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (0.0017059098161364, -0.0046113182222151, 0.00021135865606388, 0.99974639195447)
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