NonPredictionIntervalContextIgnorantAbstractModel¶
- class NonPredictionIntervalContextIgnorantAbstractModel[source]¶
Bases:
etna.models.base.AbstractModelInterface for models that don’t support prediction intervals and don’t need context for prediction.
- Inherited-members
Methods
fit(ts)Fit model.
forecast(ts[, return_components])Make predictions.
get_model()Get internal model/models that are used inside etna class.
load(path)Load an object.
params_to_tune()Get grid for tuning hyperparameters.
predict(ts[, return_components])Make predictions with using true values as autoregression context if possible (teacher forcing).
save(path)Save the object.
set_params(**params)Return new object instance with modified parameters.
to_dict()Collect all information about etna object in dict.
Attributes
Context size of the model.
- abstract forecast(ts: etna.datasets.tsdataset.TSDataset, return_components: bool = False) etna.datasets.tsdataset.TSDataset[source]¶
Make predictions.
- Parameters
ts (etna.datasets.tsdataset.TSDataset) – Dataset with features
return_components (bool) – If True additionally returns forecast components
- Returns
Dataset with predictions
- Return type
- abstract predict(ts: etna.datasets.tsdataset.TSDataset, return_components: bool = False) etna.datasets.tsdataset.TSDataset[source]¶
Make predictions with using true values as autoregression context if possible (teacher forcing).
- Parameters
ts (etna.datasets.tsdataset.TSDataset) – Dataset with features
return_components (bool) – If True additionally returns prediction components
- Returns
Dataset with predictions
- Return type
- property context_size: int¶
Context size of the model. Determines how many history points do we ask to pass to the model.
Zero for this model.