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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 8865 training rounds!
End result
Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.9947010519316, -0.0012269628404391, 0.00058418265859189, -0.0010777620671808)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.99456252465164, -0.00035726868417821, 0.0089371115824969, -6.3944370634837E-5)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (-0.016593199985008, 0.99987177981209, 0.014084166952073, 0.0012938997947711)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (0.009264523455076, 0.99986884892822, -0.0032605766467233, 0.00047365858750054)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (0.0033830891133336, -0.00063414326086976, 0.99560860900131, -0.00088395747126782)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (0.0091760260151092, -0.00013234927159407, 0.9955314818933, 0.0026522362679039)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (0.0006766416429706, -0.0001489746354976, -0.00014204007671092, 0.99982902216892)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (0.0042043207864175, -0.00024728323984883, -0.00098706283117402, 0.99982754355745)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (-0.00086495963148649, -0.00090161639135748, -0.002853084995623, 0.99983183988028)
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