bigframes.bigquery.ml.recommend#
- bigframes.bigquery.ml.recommend(model: BaseEstimator | str | Series, input_: DataFrame | DataFrame | str | None = None, *, trial_id: int | None = None) DataFrame[source]#
Generates recommendations from a BigQuery ML matrix factorization model.
See the BigQuery ML RECOMMEND function syntax for additional reference.
- Parameters:
model (bigframes.ml.base.BaseEstimator, str, or pd.Series) – The matrix factorization model to use for recommendation.
input (Union[bigframes.pandas.DataFrame, str], optional) – The DataFrame or query that contains the user and/or item data to generate recommendations for. If not provided, recommendations are returned for every user-item combination seen during training.
trial_id (int, optional) – An INT64 value that identifies the hyperparameter tuning trial that you want the function to evaluate. The function uses the optimal trial by default. Only specify this argument if you ran hyperparameter tuning when creating the model.
- Returns:
The recommendation results.
- Return type: