DOC Ensures that cross_validate passes numpydoc validation (scikit-learn#23145)

felixriese · web-flow · commit e2d120981fa8 · 2022-04-16T14:32:23.000-04:00
diff --git a/sklearn/model_selection/_validation.py b/sklearn/model_selection/_validation.py
@@ -208,6 +208,16 @@ def cross_validate(
                 This is available only if ``return_estimator`` parameter
                 is set to ``True``.
 
+    See Also
+    --------
+    cross_val_score : Run cross-validation for single metric evaluation.
+
+    cross_val_predict : Get predictions from each split of cross-validation for
+        diagnostic purposes.
+
+    sklearn.metrics.make_scorer : Make a scorer from a performance metric or
+        loss function.
+
     Examples
     --------
     >>> from sklearn import datasets, linear_model
@@ -238,17 +248,6 @@ def cross_validate(
     [-3635.5... -3573.3... -6114.7...]
     >>> print(scores['train_r2'])
     [0.28009951 0.3908844  0.22784907]
-
-    See Also
-    --------
-    cross_val_score : Run cross-validation for single metric evaluation.
-
-    cross_val_predict : Get predictions from each split of cross-validation for
-        diagnostic purposes.
-
-    sklearn.metrics.make_scorer : Make a scorer from a performance metric or
-        loss function.
-
     """
     X, y, groups = indexable(X, y, groups)
 
diff --git a/sklearn/tests/test_docstrings.py b/sklearn/tests/test_docstrings.py
@@ -81,7 +81,6 @@
     "sklearn.metrics.pairwise.polynomial_kernel",
     "sklearn.metrics.pairwise.rbf_kernel",
     "sklearn.metrics.pairwise.sigmoid_kernel",
-    "sklearn.model_selection._validation.cross_validate",
     "sklearn.model_selection._validation.learning_curve",
     "sklearn.model_selection._validation.permutation_test_score",
     "sklearn.model_selection._validation.validation_curve",
