ArimaResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)(Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results.
Attributes | |
|---|---|
| Name | Description |
arima_model_info |
Sequence[google.cloud.bigquery_v2.types.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo]
This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one. |
seasonal_periods |
Sequence[google.cloud.bigquery_v2.types.Model.SeasonalPeriod.SeasonalPeriodType]
Seasonal periods. Repeated because multiple periods are supported for one time series. |
Classes
ArimaCoefficients
ArimaCoefficients(mapping=None, *, ignore_unknown_fields=False, **kwargs)Arima coefficients.
ArimaModelInfo
ArimaModelInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)Arima model information.
Methods
__delattr__
__delattr__(key)Delete the value on the given field.
This is generally equivalent to setting a falsy value.
__eq__
__eq__(other)Return True if the messages are equal, False otherwise.
__ne__
__ne__(other)Return True if the messages are unequal, False otherwise.
__setattr__
__setattr__(key, value)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.