So let's say I have data with numerical variables
I believe that the value of
A has an effect on
I also believe that
B both have an effect on
I don't think
C has an effect on either
I want to use machine learning to predict
C. I obviously have
B as training data, and I have other variables as training data too.
Do I simply create multiple models to predict all three, or is there a way to make one model predict them all if I just throw the entire dataset at it?