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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 2976 training rounds!
End result
Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.99894819231895, -0.003224503905016, -0.0011141781871735, 0.00028705924359823)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.9989551083887, -0.0027292568018283, -0.0017535869628025, 0.0037862521990536)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (0.00064749970550084, 0.99838391141732, 0.0017809459527731, -0.001401463812571)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (-0.001150544090642, 0.99840957583635, -0.0037102179217308, -0.0019559669323334)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (-0.0043236120972198, -0.0098266498083399, 0.99810841837425, -0.0024200767348883)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (0.0095916177429248, 0.013671096557017, 0.99791558416532, 0.013329163001813)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (-0.00091366586022091, -0.0018920292520276, 0.0022886149816061, 0.99890126879289)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (-0.0008545964194773, -0.0018614998422312, -0.0017627427619908, 0.9989106705097)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (-0.00033065012655118, 0.0030044264780631, -0.0089732472926938, 0.99891529420179)
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