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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 = (0.100271181342, -0.021284525239443, 0.78653089218472, 0.000155551843058)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.10026981657109, -0.021298352944629, 0.7865312364725, 0.00017953187809819)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (0.082482903023044, 0.98656781311139, -0.10171008043707, 0.00021853015404993)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (0.082482903022025, 0.98656781311112, -0.10171008043638, 0.00021853017189521)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (0.10026981657817, -0.021298352872872, 0.78653123647071, 0.00017953175365729)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (0.1002698193788, -0.021298324497215, 0.78653123576421, 0.00017948254452078)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (-0.15609084004718, 0.08923768034346, 0.055071736379429, 0.99952791840007)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (-0.13866659428885, 0.008628371194645, 0.15528500836161, 0.99917398420806)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (-0.15985553055578, 0.050688259571118, 0.057592034325763, 0.99958724149664)
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