#neural-forecast
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Farzad E
02/21/2023, 4:49 PMIs there a way to pass exogenous features to AutoNHITS?
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Cristian (Nixtla)
02/21/2023, 4:55 PMHi @Farzad E. Yes, you need to create your own hyperparameter grid (example here: https://nixtla.github.io/neuralforecast/examples/automatic_hyperparameter_tuning.html), and specify the exogenous variables using the appropriate hyperparameter.
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Farzad E
02/21/2023, 5:35 PM@Cristian (Nixtla) so let's say your exogenous feature is week_day. Instead of passing this as a futr_exog_list as you do with NHITS, you pass this as a hyperparameter to AutoNHITS?!
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Cristian (Nixtla)
02/21/2023, 5:36 PMyou need to add it as one entry of the configuration dictionary. For example:
"futr_exog_list":your_listand you can try models with/without exogenous with:
"futr_exog_list":tune.choice([your_list,None])so its not directly to the AutoNHITS model, but to the configuration dictionary, which you then pass it to the AutoNHITS with the
config👍 1
You also need to have those variables in the dataframe
Also, for the hyperparameters you DONT specify in the config the model will use their default value (from the
NHITS👍 1
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Farzad E
02/21/2023, 5:43 PMThanks. I was confused since I knew config was for hyperparameters from the examples and I knew there were specific entries for exogenous features but I didn't know we could pass them to config. This is very helpful.
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Cristian (Nixtla)
02/21/2023, 5:45 PMsorry if it was not clear in the documentation. We will add this in the examples!
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Farzad E
02/21/2023, 5:50 PMNo worries. Documenting is very time consuming and your team has made great progress. Thanks for your contributions to open source.
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