I am currently building a neural network using Keras to perform a regression.
I have 4 independent variables
W,X,Y,Z. They are used to predict 3 different functions
Should my output layer have 1 or 3 neurons? Also, should I be using a relu or linear activation function for the output layer? I'm currently using MSE for my loss function and adam for my optimizer.
For my metrics, should I use 'accuracy' or 'r2'?
Any suggestions? I'm sorry, I'm new to deep learning...