I am a newbie to machine learning. I have an LSTM model that predicts the next output n+1
time 1, params 1, output 1
time 2, params 2, output 2
time 3, params 3, output 3
time n, params n, , output n
time n+1 --> predicts output n+1
Here the times are all in minutes, so I can predict the next output in the series which is going to be the next minute. My question is that what if I want to predict the next 5 minutes. One solution was to throw out all the data except in steps of 5 minutes so the next step is automatically would be 5 minutes. This is clearly a waste of all the data that I have gathered. Can you please recommend what I can do about the prediction on different time scales?