Training Results
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Epoch needed to Reach SSE = 35 with Training Speed of 0.1 #Hidden Nodes Weights = 0.5 Weights = Random 3 242 12 5 352 22 15 242 12 20 352 22 25 516 24 Epoch needed to Reach SSE = 35 with Training Speed of 0.5 #Hidden Nodes Weights = 0.5 Weights = Random 3 82 6 5 115 6 15 Not reached and Over train 7 20 Not reached after 820 Epochs 16 25 877 29 R^2 for each output and the sum of R^2 Max # Epoch = 1000 Training Speed = 0.1 #Hidden Nodes Weights = 0.5 Weights = Random 3 -0.259 0.730 0.864 0.986 0.503 0.929 0.998 0.999 2.106 3.644 5 -0.250 0.524 0.864 0.996 0.501 0.955 0.998 0.999 2.113 3.474 15 -0.037 0.319 0.874 0.999 0.529 0.964 0.998 0.999 2.364 3.281 20 0.092 0.217 0.880 0.999 0.557 0.968 0.998 0.999 2.527 3.183 25 0.200 0.199
description
Training results of my neural network trained with the back-propagation algorithm
Transcript of Training Results
Epoch needed to Reach SSE = 35 with Training Speed of 0.1
#Hidden NodesWeights = 0.5Weights = Random
324212
535222
1524212
2035222
2551624
Epoch needed to Reach SSE = 35 with Training Speed of 0.5
#Hidden NodesWeights = 0.5Weights = Random
3826
51156
15Not reached and Over train7
20Not reached after 820 Epochs16
2587729
R^2 for each output and the sum of R^2 Max # Epoch = 1000 Training Speed = 0.1
#Hidden NodesWeights = 0.5Weights = Random
3-0.2590.730
0.8640.986
0.5030.929
0.9980.999
2.1063.644
5-0.2500.524
0.8640.996
0.5010.955
0.9980.999
2.1133.474
15-0.0370.319
0.8740.999
0.5290.964
0.9980.999
2.3643.281
200.0920.217
0.8800.999
0.5570.968
0.9980.999
2.5273.183
250.2000.199
0.8850.999
0.5950.983
0.9980.999
2.6783.180
R^2 for each output and the sum of R^2 Max # Epoch = 1000 Training Speed = 0.3
#Hidden NodesWeights = 0.5Weights = Random
30.2300.785
0.8600.976
0.5150.702
0.9980.999
2.6033.462
5-0.2890.313
0.8610.999
0.5120.944
0.9980.999
2.0823.255
15-0.0810.345
0.8730.999
0.5480.969
0.9980.999
2.3383.312
200.0440.289
0.8790.998
0.5880.969
0.9880.999
2.4993.255
250.1410.325
0.8830.999
0.6440.964
0.9980.999
2.6163.287
