bigframes.bigquery.ml.create_model#

bigframes.bigquery.ml.create_model(model_name: str, *, replace: bool = False, if_not_exists: bool = False, transform: list[str] | None = None, input_schema: Mapping[str, str] | None = None, output_schema: Mapping[str, str] | None = None, connection_name: str | None = None, options: Mapping[str, str | int | float | bool | list | Expression] | None = None, training_data: DataFrame | DataFrame | str | None = None, custom_holiday: DataFrame | DataFrame | str | None = None, session: Session | None = None) → Series[source]#

Creates a BigQuery ML model.

See the BigQuery ML CREATE MODEL DDL syntax for additional reference.

Parameters:

• model_name (str) The name of the model in BigQuery.

• replace (bool, default False) Whether to replace the model if it already exists.

• if_not_exists (bool, default False) Whether to ignore the error if the model already exists.

• transform (list[str], optional) A list of SQL transformations for the TRANSFORM clause, which specifies the preprocessing steps to apply to the input data.

• input_schema (Mapping[str, str], optional) The INPUT clause, which specifies the schema of the input data.

• output_schema (Mapping[str, str], optional) The OUTPUT clause, which specifies the schema of the output data.

• connection_name (str, optional) The connection to use for the model.

• options (Mapping[str, Union[str, int, float, bool, list, bigframes.core.col.Expression]], optional) The OPTIONS clause, which specifies the model options.

• training_data (Union[bigframes.pandas.DataFrame, str], optional) The query or DataFrame to use for training the model.

• custom_holiday (Union[bigframes.pandas.DataFrame, str], optional) The query or DataFrame to use for custom holiday data.

• session (bigframes.session.Session, optional) The session to use. If not provided, the default session is used.

Returns:

A Series with object dtype containing the model metadata. Reference the BigQuery Model REST API reference for available fields.

Return type:

pandas.Series