Please forgive my ignorance. I'm new to deep learning and this could prove to be a "stupid" question...
I want to build a neural network that can predict some outcome "x". I have training data that contains 1000's of variables for each case. I have no idea if in the 1000's of variables is/are the real reason(s) for the outcome x.
Is my neural network useless?
If the neural network is able to predict outcome x with some degree of accuracy using test data, does that mean the real reason(s) for outcome x is/are buried somewhere in the 1000's of variables?