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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 1244 training rounds!

End result


Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.99356026519905, 6.9963043910471E-5, -0.002531712302729, 0.0013208236194397)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.99348589762453, -0.0010391738358345, -0.0019514419798454, 0.0062011875247556)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (-0.011589340009995, 0.99840044089928, -0.013924765722223, 0.0043079194249597)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (0.0093517397629746, 0.99826771645385, 0.0028589775557325, 0.0048027812042343)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (-0.00046030939828515, 0.0046681229035495, 0.99708875780212, 0.0079655589178694)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (-0.0095381934912185, -0.0041766666277992, 0.99706408858646, 0.0064793775364039)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (0.00054032880186615, 0.00014499600159263, -0.00037824676127431, 0.99784158235376)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (0.0013456918690187, 0.00058435526659359, 0.0014674823421182, 0.99782819303764)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (-0.0038127674268722, 0.00063259024902591, 0.0023762012704095, 0.99785023391106)
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