does we need to perform normalisation of predicted regression before feed it to losss function?
I want to train a model for predecting the ellipse parameters
should i need to normalise the ellipses parameters before calculating the loss between the ground truth and the predection
becouse for example if the Gthcx=200 and the prediction is 100 the distnace between them is 100 if i use mae so is that gonna affect the convergence of my model
and thank you