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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 2655 training rounds!
End result
Testset 0; expected output = (1, 0, 0, 0) output from neural network = (0.99631791669147, -0.0027656386866922, -0.0080498864961043, 0.012259414792251)
Testset 1; expected output = (1, 0, 0, 0) output from neural network = (0.99708118927678, -0.0048245015366915, 0.00048869825832124, 0.0030516738955162)
Testset 2; expected output = (0, 1, 0, 0) output from neural network = (0.0015833016223649, 0.99752317106502, -0.0051740828916797, -0.0044219419988446)
Testset 3; expected output = (0, 1, 0, 0) output from neural network = (0.00449157836573, 0.99850100216312, -0.0053070220953259, 0.0033536053315193)
Testset 4; expected output = (0, 0, 1, 0) output from neural network = (-0.00024064536749259, -0.005020837776213, 0.99875392545984, -0.0066113007046512)
Testset 5; expected output = (0, 0, 1, 0) output from neural network = (0.0021682063924885, 0.0023409126214773, 0.99735558843403, -0.00023487463834388)
Testset 6; expected output = (0, 0, 0, 1) output from neural network = (0.0016807843659382, -0.0021240383302456, -0.0015051749391802, 0.99917685315716)
Testset 7; expected output = (0, 0, 0, 1) output from neural network = (-0.0020543533793702, -0.0011027372857461, 0.0073123393573287, 0.99916133025576)
Testset 8; expected output = (0, 0, 0, 1) output from neural network = (-0.0032110814950006, -0.00028104320693444, -0.007494964139011, 0.99922988523281)
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