TimeSeriesDataFrame.get_model_inputs_for_scoring

TimeSeriesDataFrame.get_model_inputs_for_scoring(prediction_length: int, known_covariates_names: List[str] | None = None) → Tuple[TimeSeriesDataFrame, TimeSeriesDataFrame | None][source]

Prepare model inputs necessary to predict the last prediction_length time steps of each time series in the dataset.

Parameters:

  • prediction_length (int) – The forecast horizon, i.e., How many time steps into the future must be predicted.

  • known_covariates_names (List[str], optional) – Names of the dataframe columns that contain covariates known in the future. See known_covariates_names of TimeSeriesPredictor for more details.

Returns:

  • past_data (TimeSeriesDataFrame) – Data, where the last prediction_length time steps have been removed from the end of each time series.

  • known_covariates (TimeSeriesDataFrame or None) – If known_covariates_names was provided, dataframe with the values of the known covariates during the forecast horizon. Otherwise, None.