Open hberande opened 8 months ago
Hi @hberande,
As explained in the table summarizing the models available in darts here, NBEATS and NHiTs do not support future covariates at the moment.
I don't think that modifying these models architectures to support such covariates is a priority at the moment, it might come in future releases if someone takes the time to implement it.
Hi @madtoinou, Thanks for the prompt response. Is it possible to implement this at my level?
It should be, but you might diverge from the initial architecture and there is no guarantee of performance gain. Be careful about data leakage.
DLinearModel
and NLinearModel
model.It looks like NHITS now supports future covariates. From the nixtla implementation:
https://github.com/Nixtla/neuralforecast/blob/main/nbs/models.nhits.ipynb
#| export
class NHITS(BaseWindows):
""" NHITS
The Neural Hierarchical Interpolation for Time Series (NHITS), is an MLP-based deep
neural architecture with backward and forward residual links. NHITS tackles volatility and
memory complexity challenges, by locally specializing its sequential predictions into
the signals frequencies with hierarchical interpolation and pooling.
**Parameters:**
`h`: int, Forecast horizon.
`input_size`: int, autorregresive inputs size, y=[1,2,3,4] input_size=2 -> y_[t-2:t]=[1,2].
`stat_exog_list`: str list, static exogenous columns.
`hist_exog_list`: str list, historic exogenous columns.
`futr_exog_list`: str list, future exogenous columns.
...
Hi, presently I'm getting the good accuracy for my data using "NBEATS & N-Hits" Models from Darts library. But I am also want to use "future_covariates" to above models. Is there any possibility to do so in the current version or in future??