If a single output is predicted by an RNN at the end of a timeseries, frequently the outputs of each timestep of the RNN are averaged to make this prediction. My impression is that it seems strange, but it works.
Suppose an output needs to be predicted for each of n timesteps. Does it therefore make sense to use the average of outputs 1,..,k for prediction k<=n so as to generalize the above?
I would be interested if anyone has convincing evidence or opinions one way or the other.