I'm relatively new to machine learning, and I don't know what error I should use for an RNN.
I want to use a simple Elman RNN to predict the cases of Covid-19 there will be in a hospital for the next 15 days. I modeled this as a regression problem, treating the input like a bunch of dots in a graph to predict the tendency that the data is going to take (only show if there will be more cases or less).
With that bunch of dots I in fact refer to this:
Then I would treat this problem as a regression.
I actually don't have anything programmed yet. Firstly I want to write it all on a paper and then get down to work. I am also considering focusing the problem to predict the actual plot of the time-series input, but right now I want to try the regression.
I've come to the conclusion that I can use these four different errors:
What are the different characteristics of these errors? Which to use? Where and when to use them?