Back to models
Forecaster

OnlineEnsembleForecaster

API referenceSource
Categorical featuresIn-sample predictionsIn-sample prediction intervals

Online Updating Ensemble of forecasters.

Quickstart

python
from sktime.forecasting.online_learning import OnlineEnsembleForecaster

estimator = OnlineEnsembleForecaster(forecasters, ensemble_algorithm=None, n_jobs=None)

Tags

Capabilities

  • Categorical features
  • In-sample predictions: Supported
  • In-sample prediction intervals: Supported
  • Prediction intervals: Not supported
  • Missing values: Not supported
  • Exogenous variables: Not supported
  • Multivariate: Not supported

Properties

Needs forecast horizon in fitrequires-fh-in-fit
No
X and y need the same indexX-y-must-have-same-index
Yes

Parameters(3)

ensemble_algorithmensemble algorithm
forecasterslist of estimator, (str, estimator), or (str, estimator, count) tuples

Estimators to apply to the input series.

  • (str, estimator) tuples: the string is a name for the estimator.

  • estimator without string will be assigned unique name based on class name

  • (str, estimator, count) tuples: the estimator will be replicated count times.

n_jobsint or None, optional (default=None)
The number of jobs to run in parallel for fit. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors.