#neural-forecast
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Chris Gervais
02/08/2023, 8:52 PMis it possible to use NHITS to forecast future periods if we don't have "live"
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Kin Gtz. Olivares
02/08/2023, 8:57 PMHi @Chris Gervais ,
That is the “cold-start” problem.
Although we have not explored that functionality. In principle neural forecast methods should be able of making such predictions.
The most important input for the “cold start” problem are the static features.
As long as other series with similar static features are available in your dataset a prediction with no temporal information should be feasible.
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Chris Gervais
02/08/2023, 9:01 PMi think i may have misrepresented the problem 🙂 we have lots of y values historically, say from jan - dec 2022, as well as plenty of future exogenous variables. but we have no
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Kin Gtz. Olivares
02/08/2023, 9:18 PMA bit more like a missing data problem?
Would you be able to create predictions and feed the predictions to the model in rolling window fashion?
Or for such series with missing values fit and predict a long horizon and drop the predictions with the missing lags?
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Chris Gervais
02/08/2023, 9:34 PMgood question, it might be possible. would it help if we provided some sample data from fitting + the input data frames?