I have a loss function that minimizes the error according to what I want the neural network to do. The problem is, that it is a nondifferentiable function. How can I handle this?
the loss function: $(1-y) \cdot log(1-p) + min((1-y)-(y \cdot log(p)))$
- $y$: target
- $p$: prediction
I have tried to smooth the minimum, but I am not sure this is good enough. As you can see, the min operator is nondifferentiable
How to handle a nondifferentiable loss function with Neural Networks?
pare in this context? $\endgroup$