diff --git a/maint_tools/test_docstrings.py b/maint_tools/test_docstrings.py
index e621ba12dcb11..d7d5317d14106 100644
--- a/maint_tools/test_docstrings.py
+++ b/maint_tools/test_docstrings.py
@@ -150,7 +150,6 @@
     "RadiusNeighborsRegressor",
     "RadiusNeighborsTransformer",
     "RandomForestClassifier",
-    "RandomForestRegressor",
     "RandomTreesEmbedding",
     "RandomizedSearchCV",
     "RegressorChain",
diff --git a/sklearn/ensemble/_forest.py b/sklearn/ensemble/_forest.py
index 2517589ef5440..fa3567370cd18 100644
--- a/sklearn/ensemble/_forest.py
+++ b/sklearn/ensemble/_forest.py
@@ -276,7 +276,6 @@ def decision_path(self, X):
         n_nodes_ptr : ndarray of shape (n_estimators + 1,)
             The columns from indicator[n_nodes_ptr[i]:n_nodes_ptr[i+1]]
             gives the indicator value for the i-th estimator.
-
         """
         X = self._validate_X_predict(X)
         indicators = Parallel(
@@ -319,6 +318,7 @@ def fit(self, X, y, sample_weight=None):
         Returns
         -------
         self : object
+            Fitted estimator.
         """
         # Validate or convert input data
         if issparse(y):
@@ -613,6 +613,13 @@ def feature_importances_(self):
     )
     @property
     def n_features_(self):
+        """Number of features when fitting the estimator.
+
+        Returns
+        -------
+        n_features_in_ : int
+            The number of features when fitting the estimator.
+        """
         return self.n_features_in_
 
 
@@ -1594,7 +1601,9 @@ class RandomForestRegressor(ForestRegressor):
 
     See Also
     --------
-    DecisionTreeRegressor, ExtraTreesRegressor
+    sklearn.tree.DecisionTreeRegressor : A decision tree regressor.
+    sklearn.ensemble.ExtraTreesRegressor : Ensemble of extremely randomized
+        tree regressors.
 
     Notes
     -----