Class ArimaResult (2.20.0)

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.

builtins.object > proto.message.Message > ArimaResult

ArimaCoefficients(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Arima coefficients. .. attribute:: auto_regressive_coefficients

Auto-regressive coefficients, an array of double.

:type: Sequence[float]

ArimaModelInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Arima model information. .. attribute:: non_seasonal_order

Non-seasonal order.

__delattr__(key)

Delete the value on the given field.

This is generally equivalent to setting a falsy value.

__eq__(other)

Return True if the messages are equal, False otherwise.

__ne__(other)

Return True if the messages are unequal, False otherwise.

__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.