I'm training a neural network. Normalization of inputs and outputs (training data) is carried out using min and max to a scale of [0-1].
I'm applying backpropagation learning algorithm. I need to get the error offset. i.e. error = actual output $-$ output
How do I scale my output [0-1] back to actual real values such as in zero to thousands range?