ArimaSingleModelForecastingMetrics( mapping=None, *, ignore_unknown_fields=False, **kwargs )
Model evaluation metrics for a single ARIMA forecasting model.
Arima fitting metrics.
Is arima model fitted with drift or not. It is always false when d is not 1.
The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
Seasonal periods. Repeated because multiple periods are supported for one time series.
If true, holiday_effect is a part of time series decomposition result.
If true, spikes_and_dips is a part of time series decomposition result.
If true, step_changes is a part of time series decomposition result.
Inheritancebuiltins.object > proto.message.Message > ArimaSingleModelForecastingMetrics
Delete the value on the given field.
This is generally equivalent to setting a falsy value.
Return True if the messages are equal, False otherwise.
Return True if the messages are unequal, False otherwise.
Set the value on the given field.
For well-known protocol buffer types which are marshalled, either the protocol buffer object or the Python equivalent is accepted.