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#neural-forecast
Title
# neural-forecast
a

Andrei Tulbure

01/04/2023, 10:01 PM
Hi! What would be the best way to use a NeuralForecast object to test out predictions from AutoTFT, AutoNBEATS, Auto NHiTs? I do see a cross validation module which is great but I do not see any .Forecast method. Should I only use .predict () ?
k

Kin Gtz. Olivares

01/04/2023, 11:16 PM
Hi @Andrei Tulbure, You are right, using the
NeuralForecast.predict
method without additional arguments is analogous to forecast. The Automatic Forecasting methods are low level classes that operate purely with PyTorch and Numpy. For comparison of the
AutoTFT
,
AutoNBEATS
, and
AutoNHITS
we recommend you to use directly the
NeuralForecast
high-level wrapper class and its methods. Here is a
NeuralForecast
class documentation and usage example: • https://nixtla.github.io/neuralforecast/core.htmlhttps://nixtla.github.io/neuralforecast/examples/longhorizon_with_nhits.html I opened this issue: https://github.com/Nixtla/neuralforecast/issues/394
a

Andrei Tulbure

01/05/2023, 10:33 AM
Great! Thanks a lot! Another question, when do you think you would be able to also have an AutoNBeatsx ?
Because exogeneous variables seem very important to my data
k

Kin Gtz. Olivares

01/05/2023, 1:35 PM
Hi @Andrei Tulbure, For the moment we don't have
AutoNBEATSx
, thanks for noticing it. We opened an issue for it. You can still recover an
AutoNBEATSx
-like behavior with the
AutoNHITS
model by setting
n_freq_downsample
to a list of ones. The
AutoNHITS
model already accepts, static, past and future exogenous data. Here is an example: https://github.com/Nixtla/neuralforecast/blob/main/nbs/examples/Exogenous_Variables.ipynb
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Andrei Tulbure

01/05/2023, 2:39 PM
Thanks!
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