From eeb0f684f1bb75d765c1bbc5fc2ce9b8eea57ae9 Mon Sep 17 00:00:00 2001
From: Pavel Guzenfeld <pavelguzenfeld@gmail.com>
Date: Fri, 20 Mar 2026 00:42:57 +0200
Subject: [PATCH 1/2] [python-package] Replace bare Any with specific types in
 sklearn.py

Replace generic Any annotations with ArrayLike for data parameters
and DMatrix for return types in internal helper functions:

- _wrap_evaluation_matrices: 13 params Any -> ArrayLike, return
  Tuple[Any, ...] -> Tuple[DMatrix, List[Tuple[DMatrix, str]]]
- pick_ref_categories: X param Any -> ArrayLike
- invalid_type: m param Any -> object

Remaining Any usages (**kwargs, Dict[str, Any] for params) are
intentional as they represent genuinely heterogeneous data.

Follow-up to #6496.
---
 python-package/xgboost/sklearn.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/python-package/xgboost/sklearn.py b/python-package/xgboost/sklearn.py
index b49f0ae85fcc..400d7d8214f9 100644
--- a/python-package/xgboost/sklearn.py
+++ b/python-package/xgboost/sklearn.py
@@ -649,7 +649,7 @@ def get_model_categories(
 
 
 def pick_ref_categories(
-    X: Any,
+    X: ArrayLike,
     model_cats: Optional[Union[FeatureTypes, Categories]],
     Xy_cats: Optional[Categories],
 ) -> Optional[Union[FeatureTypes, Categories]]:
@@ -682,22 +682,22 @@ def pick_ref_categories(
 def _wrap_evaluation_matrices(
     *,
     missing: float,
-    X: Any,
-    y: Any,
-    group: Optional[Any],
-    qid: Optional[Any],
-    sample_weight: Optional[Any],
-    base_margin: Optional[Any],
+    X: ArrayLike,
+    y: ArrayLike,
+    group: Optional[ArrayLike],
+    qid: Optional[ArrayLike],
+    sample_weight: Optional[ArrayLike],
+    base_margin: Optional[ArrayLike],
     feature_weights: Optional[ArrayLike],
-    eval_set: Optional[Sequence[Tuple[Any, Any]]],
-    sample_weight_eval_set: Optional[Sequence[Any]],
-    base_margin_eval_set: Optional[Sequence[Any]],
-    eval_group: Optional[Sequence[Any]],
-    eval_qid: Optional[Sequence[Any]],
+    eval_set: Optional[Sequence[Tuple[ArrayLike, ArrayLike]]],
+    sample_weight_eval_set: Optional[Sequence[ArrayLike]],
+    base_margin_eval_set: Optional[Sequence[ArrayLike]],
+    eval_group: Optional[Sequence[ArrayLike]],
+    eval_qid: Optional[Sequence[ArrayLike]],
     create_dmatrix: Callable,
     enable_categorical: bool,
     feature_types: Optional[Union[FeatureTypes, Categories]],
-) -> Tuple[Any, List[Tuple[Any, str]]]:
+) -> Tuple[DMatrix, List[Tuple[DMatrix, str]]]:
     """Convert array_like evaluation matrices into DMatrix. Perform sanity checks on the
     way.
 
@@ -1209,7 +1209,7 @@ def custom_metric(m: Callable) -> Metric:
                 wrapped = _metric_decorator(m)
             return wrapped
 
-        def invalid_type(m: Any) -> None:
+        def invalid_type(m: object) -> None:
             msg = f"Invalid type for the `eval_metric`: {type(m)}"
             raise TypeError(msg)
 

From 1b1a4ee8ffece27ec39745d60923a2d46ca7765f Mon Sep 17 00:00:00 2001
From: Pavel Guzenfeld <pavelguzenfeld@gmail.com>
Date: Fri, 20 Mar 2026 01:05:17 +0200
Subject: [PATCH 2/2] Keep return type as Any since DaskDMatrix does not extend
 DMatrix

---
 python-package/xgboost/sklearn.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/python-package/xgboost/sklearn.py b/python-package/xgboost/sklearn.py
index 400d7d8214f9..e253741334e6 100644
--- a/python-package/xgboost/sklearn.py
+++ b/python-package/xgboost/sklearn.py
@@ -697,7 +697,7 @@ def _wrap_evaluation_matrices(
     create_dmatrix: Callable,
     enable_categorical: bool,
     feature_types: Optional[Union[FeatureTypes, Categories]],
-) -> Tuple[DMatrix, List[Tuple[DMatrix, str]]]:
+) -> Tuple[Any, List[Tuple[Any, str]]]:
     """Convert array_like evaluation matrices into DMatrix. Perform sanity checks on the
     way.