ArimaForecastingMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Model evaluation metrics for ARIMA forecasting models.
Arima model fitting metrics.
Seasonal periods. Repeated because multiple periods are supported for one time series.
Whether Arima model fitted with drift or not. It is always false when d is not 1.
Id to differentiate different time series for the large-scale case.
Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
Inheritancebuiltins.object > proto.message.Message > ArimaForecastingMetrics
ArimaSingleModelForecastingMetrics( mapping=None, *, ignore_unknown_fields=False, **kwargs )
Model evaluation metrics for a single ARIMA forecasting model.
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.