reorganize the commit

bigframes/ml/ensemble.py

@@ -507,11 +507,6 @@ def score(
     ):
         """Calculate evaluation metrics of the model.
 
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
-
         Args:
             X (bigframes.dataframe.DataFrame or bigframes.series.Series):
                 A BigQuery DataFrame as evaluation data.
@@ -681,11 +676,6 @@ def score(
     ):
         """Calculate evaluation metrics of the model.
 
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
-
         Args:
             X (bigframes.dataframe.DataFrame or bigframes.series.Series):
                 A BigQuery DataFrame as evaluation data.

bigframes/ml/forecasting.py

@@ -112,11 +112,6 @@ def score(
     ) -> bpd.DataFrame:
         """Calculate evaluation metrics of the model.
 
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
-
         Args:
             X (bigframes.dataframe.DataFrame or bigframes.series.Series):
                 A BigQuery DataFrame only contains 1 column as

third_party/bigframes_vendored/sklearn/base.py

@@ -85,11 +85,6 @@ def score(self, X, y):
         which is a harsh metric since you require for each sample that
         each label set be correctly predicted.
 
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
-
         Args:
             X (bigframes.dataframe.DataFrame or bigframes.series.Series):
                 DataFrame of shape (n_samples, n_features). Test samples.
@@ -110,12 +105,7 @@ class RegressorMixin:
     _estimator_type = "regressor"
 
     def score(self, X, y):
-        """Calculate evaluation metrics of the model.
-
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
+        """Return the evaluation metrics of the model.
 
         Args:
             X (bigframes.dataframe.DataFrame or bigframes.series.Series):

third_party/bigframes_vendored/sklearn/cluster/_kmeans.py

@@ -82,12 +82,7 @@ def score(
         X,
         y=None,
     ):
-        """Calculate evaluation metrics of the model.
-
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
+        """Metrics of the model.
 
         Args:
             X (bigframes.dataframe.DataFrame or bigframes.series.Series):

third_party/bigframes_vendored/sklearn/decomposition/_pca.py

@@ -55,12 +55,7 @@ def fit(self, X, y=None):
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
     def score(self, X=None, y=None):
-        """Calculate evaluation metrics of the model.
-
-        .. note::
-
-            We're using BigQuery ML.EVALUATE function (https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-evaluate)
-            for evaluateing model metrics.
+        """Return the metrics of the model.
 
         Args:
             X (default None):