PerSegmentPredictionIntervalModel

class PerSegmentPredictionIntervalModel(base_model: Any)[source]

Bases: etna.models.base.PerSegmentBaseModel, etna.models.base.PredictIntervalAbstractModel

Class for holding specific models for per-segment prediction which are able to build prediction intervals.

Init PerSegmentPredictionIntervalModel.

Parameters

base_model (Any) – Internal model which will be used to forecast segments, expected to have fit/predict interface

Inherited-members

Methods

fit(ts)

Fit model.

forecast(ts[, prediction_interval, quantiles])

Make predictions.

get_model()

Get internal models that are used inside etna class.
forecast(ts: etna.datasets.tsdataset.TSDataset, prediction_interval: bool = False, quantiles: Sequence[float] = (0.025, 0.975)) → etna.datasets.tsdataset.TSDataset[source]

Make predictions.

Parameters

  • ts (etna.datasets.tsdataset.TSDataset) – Dataset with features

  • prediction_interval (bool) – If True returns prediction interval for forecast

  • quantiles (Sequence[float]) – Levels of prediction distribution. By default 2.5% and 97.5% are taken to form a 95% prediction interval

Returns

Dataset with predictions

Return type

etna.datasets.tsdataset.TSDataset