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Hi @Anna-Maria K.! The library does not support his option currently, it will predict the immediate data after the train/validation set. The easiest solution is to increase the horizon to account for the gap. Be careful, however, that changing the

n_windows

and

step_size

are very different to the

horizon

. It seems that if you do not have September's data, you will need to have 1 window,

n_windows=1

, with a large horizon.

Thanks a lot for the clarifications!