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Another topic that may be worth talking about, add a function to the library, and potentially document it, is how to constraint the Forecasts.
For example, in my case, my dataset has always a target value y positives.
So I am looking how to constraint my forecaster to forecast only positive values. When trying to perform the automatic forecasts in function of a database, often I get models forecasting negative values, which doesn't make sense (think of y such as Pressure value or ... )
Does the library has a function that allow to do this ? One way is maybe add a Log transform then Exp reverter.
The text was updated successfully, but these errors were encountered:
The prophet model has something that allows you to define a model's "floor" when using logistic growth, but I'm not sure there is a good way to generally apply such an idea to all models. Artificially constraining point estimates can lead to unforeseen biases. Furthermore, applying transformations makes it hard to determine what values should be allowed to keep the final-evaluated points below or above a certain threshold. If you have a specific idea to modify the code to allow what you are asking for, I can take a look at it. Otherwise, this isn't something I will plan to work on.
Another topic that may be worth talking about, add a function to the library, and potentially document it, is how to constraint the Forecasts.
For example, in my case, my dataset has always a target value
y
positives.So I am looking how to constraint my forecaster to forecast only positive values. When trying to perform the automatic forecasts in function of a database, often I get models forecasting negative values, which doesn't make sense (think of y such as Pressure value or ... )
Does the library has a function that allow to do this ? One way is maybe add a Log transform then Exp reverter.
The text was updated successfully, but these errors were encountered: