Andrei Tulbure
01/04/2023, 10:01 PMKin Gtz. Olivares
01/04/2023, 11:16 PMNeuralForecast.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.html
• https://nixtla.github.io/neuralforecast/examples/longhorizon_with_nhits.html
I opened this issue: https://github.com/Nixtla/neuralforecast/issues/394Andrei Tulbure
01/05/2023, 10:33 AMKin Gtz. Olivares
01/05/2023, 1:35 PMAutoNBEATSx
, 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.ipynbAndrei Tulbure
01/05/2023, 2:39 PM