Can I use weights and bias to manually verify the feedforwardnet?
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I have 20 input and 20 target. I build feedforwardnet with one hidden layer of 10 neurons. I got "input weight (IW)" size of 10*20, "layer weight (LW)" size of 20*10. First bias size 10*1, second bias size 20*1.
I am trying to use Excel to manully calcuate the output step-by-step, so as to fully understand the procedure. What I do in Excel is (MMULT is the matrix multiplication function in Excel):
- MMULT(20 input, IW) = 10 elements
- 10 elements + First bias 10*1 = 10 elements
- tanh(10 elements) = 10 elements
- MMULT(10 elements, LW) = 20 elements
- 20 elements + second bias 20*1 = 20 elements
I can do the calculation based on the above steps. However, the final results differ a lot from the MatLab's prediction. I can get the exact result by using Pytorch's weights and bias. Is "Tanh" the default activation function in feedforwardnet?
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Steven Lord
2021-4-26
Don't forget the pre- and post-processing steps.
net = feedforwardnet(10);
net.inputs{1}
In this case that would be removeconstantrows and mapminmax. Also see the net.outputs property.
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