Open ryzenX opened 6 years ago
the output is squashed to be between 0 and 1, because of the sigmoid function at the end. As such, this network in its current form only predicts a class label of 0 or 1. You'd need to remove the sigmoid function at the end, and tweak the backpropagation if you want to use it to do addition.
Hello, it's possible to use your neural network for addition of integer/float with result > 1 ? like this :
when i search 1+3:
neural_network.forward_pass(array([1,3]))
i have in output 0.99, what do I have to change in the code to do that?