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Hi, as an analogy, imagine that today i have say 10 years of daily temperatures, i train a model with a forecast horizon of 7 so i predict the temperature forecast for 1 week.
So tomorrow comes, and i have a new temperature data point.
What do i input as data for a new 7 day forecast?
prediction = predict_model(loaded_model, X=data)
Will data be just tomorrow's temperature?
or do i need a much larger data set including tomorrows temperature for a good prediction?
(Note: Its just an analogy, i'm just trying to get my head my head around how to use a saved time_series model)
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