diff --git a/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py b/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py
index 24d8a55df4f7d..38ff9a7ba3ba2 100644
--- a/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py
+++ b/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py
@@ -1579,7 +1579,7 @@ class HistGradientBoostingRegressor(RegressorMixin, BaseHistGradientBoosting):
     scoring : str or callable or None, default='loss'
         Scoring parameter to use for early stopping. It can be a single
         string (see :ref:`scoring_parameter`) or a callable (see
-        :ref:`scoring`). If None, the estimator's default scorer is used. If
+        :ref:`scoring_callable`). If None, the estimator's default scorer is used. If
         ``scoring='loss'``, early stopping is checked w.r.t the loss value.
         Only used if early stopping is performed.
     validation_fraction : int or float or None, default=0.1
@@ -1961,7 +1961,7 @@ class HistGradientBoostingClassifier(ClassifierMixin, BaseHistGradientBoosting):
     scoring : str or callable or None, default='loss'
         Scoring parameter to use for early stopping. It can be a single
         string (see :ref:`scoring_parameter`) or a callable (see
-        :ref:`scoring`). If None, the estimator's default scorer
+        :ref:`scoring_callable`). If None, the estimator's default scorer
         is used. If ``scoring='loss'``, early stopping is checked
         w.r.t the loss value. Only used if early stopping is performed.
     validation_fraction : int or float or None, default=0.1