title: Machine learning with a "function" that may have two or more outputs
body: <p>Let's say I want to model the <code>sqrt</code> function with a neural network. But for every input <code>x</code>, there are two answers <code>sqrt(x) = y</code> and <code>sqrt(x) = -y</code>. (But in reality, I don't know that I have the <code>sqrt</code> function - I just have a lot of data - so I don't know a priori if there are 0, 1, 2, or more answers <code>y</code> for every input <code>x</code>.) How can I get the correct distribution of <code>y</code>? </p>