scikit-learn · adrinjalali · Feb 13, 2025 · Jan 26, 2025 · Feb 3, 2025 · Feb 4, 2025
diff --git a/bench_num_threads.parquet b/bench_num_threads.parquet
diff --git a/examples/inspection/plot_partial_dependence.py b/examples/inspection/plot_partial_dependence.py
@@ -365,8 +365,11 @@
 # However, it is worth noting that we are creating potential meaningless
 # synthetic samples if features are correlated.
 #
+# .. _ice-vs-pdp:
+#
 # ICE vs. PDP
 # ~~~~~~~~~~~
+#
 # PDP is an average of the marginal effects of the features. We are averaging the
 # response of all samples of the provided set. Thus, some effects could be hidden. In
 # this regard, it is possible to plot each individual response. This representation is

diff --git a/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py b/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py
@@ -1563,6 +1563,8 @@ class HistGradientBoostingRegressor(RegressorMixin, BaseHistGradientBoosting):
        and specifies that each branch of a tree will either only split
         on features 0 and 1 or only split on features 2, 3 and 4.
 
+        See :ref:`this example<ice-vs-pdp>` on how to use `interaction_cst`.
+
         .. versionadded:: 1.2
 
     warm_start : bool, default=False
@@ -1908,8 +1910,8 @@ class HistGradientBoostingClassifier(ClassifierMixin, BaseHistGradientBoosting):
         .. versionchanged:: 1.4
            Added `"from_dtype"` option.
 
-        .. versionchanged::1.6
-           The default will changed from `None` to `"from_dtype"`.
+        .. versionchanged:: 1.6
+           The default value changed from `None` to `"from_dtype"`.
 
     monotonic_cst : array-like of int of shape (n_features) or dict, default=None
         Monotonic constraint to enforce on each feature are specified using the
@@ -1950,6 +1952,8 @@ class HistGradientBoostingClassifier(ClassifierMixin, BaseHistGradientBoosting):
         and specifies that each branch of a tree will either only split
         on features 0 and 1 or only split on features 2, 3 and 4.
 
+        See :ref:`this example<ice-vs-pdp>` on how to use `interaction_cst`.
+
         .. versionadded:: 1.2
 
     warm_start : bool, default=False

diff --git a/sklearn/inspection/_partial_dependence.py b/sklearn/inspection/_partial_dependence.py
@@ -385,7 +385,9 @@ def partial_dependence(
     the average response of an estimator for each possible value of the
     feature.
 
-    Read more in the :ref:`User Guide <partial_dependence>`.
+    Read more in
+    :ref:`sphx_glr_auto_examples_inspection_plot_partial_dependence.py`
+    and the :ref:`User Guide <partial_dependence>`.
 
     .. warning::
 

diff --git a/sklearn/inspection/_plot/partial_dependence.py b/sklearn/inspection/_plot/partial_dependence.py
@@ -284,7 +284,9 @@ def from_estimator(
         marks on the x-axes for one-way plots, and on both axes for two-way
         plots.
 
-        Read more in the :ref:`User Guide <partial_dependence>`.
+        Read more in
+        :ref:`sphx_glr_auto_examples_inspection_plot_partial_dependence.py`
+        and the :ref:`User Guide <partial_dependence>`.
 
         .. note::