So in this lecture, we will discuss a common misconception regarding how to forecast between the train
and test sets.
In these videos, we forecasted only four time steps within the test set for which we had true data.
But what if we would like to forecast beyond this period for which we do not have true data?
I'll present this as a quiz.
So if you had this question, please think about it for a day or so and try to implement it yourself
before moving on.
Okay.
So the answer is nothing changes.
Remember that the model does not even use the test data for anything.
So if you were thinking that the test data was used to make the forecast, this is incorrect.
The test data is not used during the forecast.
It is only used to compute our forecast metrics.
In addition, remember that the whole purpose of splitting data into train and test or train and validation
is to emulate how our model would perform on data out of sample.
Therefore, the process should be exactly the same as how we would do a real forecast into the future,
since that is what we are trying to emulate.