scikit-learn
diff --git a/‎sklearn/model_selection/_validation.py
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+10-11Lines changed: 10 additions & 11 deletions b/‎sklearn/model_selection/_validation.py
Copy file name to clipboardExpand all lines: sklearn/model_selection/_validation.py
+10-11Lines changed: 10 additions & 11 deletions
diff --git a/‎sklearn/tests/test_docstrings.py
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-1Lines changed: 0 additions & 1 deletion b/‎sklearn/tests/test_docstrings.py
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-1Lines changed: 0 additions & 1 deletion
@@ -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)
 
 
@@ -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",