I am trying to use a LSTM for time series prediction. The data streams in once per minute, but I would like to predict an hour ahead. There are two ways I can think of for going about this:
- Squash the data into hourly data instead, taking the average over each 60 minute time period as one data point.
- For each
(X, y)training data pair, let
Xbe the time series from
t - 120to
t - 60, and let
ybe the time series from
t - 60to
t. Force the LSTM to predict 60 timesteps ahead, and take
y[-1]as the prediction.
Are there any best practices for going about this?