gluonts.model.estimator module#
- class gluonts.model.estimator.DummyEstimator(predictor_cls: type, **kwargs)[source]#
Bases:
gluonts.model.estimator.Estimator
An Estimator that, upon training, simply returns a pre-constructed Predictor.
- Parameters
predictor_cls – Predictor class to instantiate.
**kwargs – Keyword arguments to pass to the predictor constructor.
- lead_time: int#
- prediction_length: int#
- train(training_data: gluonts.dataset.Dataset, validation_data: Optional[gluonts.dataset.Dataset] = None) gluonts.model.predictor.Predictor [source]#
Train the estimator on the given data.
- Parameters
training_data – Dataset to train the model on.
validation_data – Dataset to validate the model on during training.
- Returns
The predictor containing the trained model.
- Return type
- class gluonts.model.estimator.Estimator(lead_time: int = 0, **kwargs)[source]#
Bases:
object
An abstract class representing a trainable model.
The underlying model is trained by calling the train method with a training Dataset, producing a Predictor object.
- lead_time: int#
- prediction_length: int#
- train(training_data: gluonts.dataset.Dataset, validation_data: Optional[gluonts.dataset.Dataset] = None) gluonts.model.predictor.Predictor [source]#
Train the estimator on the given data.
- Parameters
training_data – Dataset to train the model on.
validation_data – Dataset to validate the model on during training.
- Returns
The predictor containing the trained model.
- Return type