Confused about terms in backpropagation calculation
On the Backpropagation Mathematics tab, it goes into the derivation of the update rule for the output layer. Right before section 5, I was wondering about how it got from (y_j - t_j)y_j(1 - y_j)h_i to \delta_j h_i (not sure if we can input equations here). I think I'm unclear as to how \delta_j is defined, I assumed it was the error y_j - t_j, but then there's an extra y_j(1 - y_j). Thanks!
3 answers ( 0 marked as helpful)
HI Emily,
What you are referring to is the derivative of the L2-norm, I believe.
Either way, sending screenshots of the exact problems would be much better!
Best,
The 365 Team
The 365 Team
HI Emily,
What you are referring to is the derivative of the L2-norm, I believe.
Either way, sending screenshots of the exact problems would be much better!
Best,
The 365 Team
The 365 Team
https://imgur.com/a/GRQEtiw
^Here is a link to a screenshot of the image. I understood the separate components but not them together.
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