bigframes.ml.linear_model.LinearRegression.score#
- LinearRegression.score(X: DataFrame | Series | DataFrame | Series, y: DataFrame | Series | DataFrame | Series) DataFrame[source]#
Calculate evaluation metrics of the model.
Note
Output matches that of the BigQuery ML.EVALUATE function. See: https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate#regression_models for the outputs relevant to this model type.
- Parameters:
X (bigframes.dataframe.DataFrame or bigframes.series.Series) – Series or DataFrame of shape (n_samples, n_features). Test samples. For some estimators this may be a precomputed kernel matrix or a list of generic objects instead with shape
(n_samples, n_samples_fitted), wheren_samples_fittedis the number of samples used in the fitting for the estimator.y (bigframes.dataframe.DataFrame or bigframes.series.Series) – Series or DataFrame of shape (n_samples,) or (n_samples, n_outputs). True values for X.
- Returns:
A DataFrame of the evaluation result.
- Return type: