scikit-learn
diff --git a/‎doc/whats_new/v1.2.rst
+3 b/‎doc/whats_new/v1.2.rst
+3
diff --git a/‎sklearn/tests/test_docstring_parameters.py
+2-2 b/‎sklearn/tests/test_docstring_parameters.py
+2-2
diff --git a/‎sklearn/tests/test_metaestimators.py
+2-2 b/‎sklearn/tests/test_metaestimators.py
+2-2
@@ -581,6 +581,9 @@ Changelog
   in version 1.4.
   :pr:`23834` by :user:`Meekail Zain <micky774>`
 
+- |FIX| :func:`utils.estimator_checks.check_estimator` now takes into account
+  the `requires_positive_X` tag correctly. :pr:`24667` by `Thomas Fan`_.
+
 Code and Documentation Contributors
 -----------------------------------
 
 
@@ -18,7 +18,7 @@
 from sklearn.utils._testing import ignore_warnings
 from sklearn.utils import all_estimators
 from sklearn.utils.estimator_checks import _enforce_estimator_tags_y
-from sklearn.utils.estimator_checks import _enforce_estimator_tags_x
+from sklearn.utils.estimator_checks import _enforce_estimator_tags_X
 from sklearn.utils.estimator_checks import _construct_instance
 from sklearn.utils.fixes import sp_version, parse_version
 from sklearn.utils.deprecation import _is_deprecated
@@ -300,7 +300,7 @@ def test_fit_docstring_attributes(name, Estimator):
         )
 
         y = _enforce_estimator_tags_y(est, y)
-        X = _enforce_estimator_tags_x(est, X)
+        X = _enforce_estimator_tags_X(est, X)
 
     if "1dlabels" in est._get_tags()["X_types"]:
         est.fit(y)
 
@@ -9,7 +9,7 @@
 from sklearn.base import is_regressor
 from sklearn.datasets import make_classification
 from sklearn.utils import all_estimators
-from sklearn.utils.estimator_checks import _enforce_estimator_tags_x
+from sklearn.utils.estimator_checks import _enforce_estimator_tags_X
 from sklearn.utils.estimator_checks import _enforce_estimator_tags_y
 from sklearn.utils.validation import check_is_fitted
 from sklearn.utils._testing import set_random_state
@@ -289,7 +289,7 @@ def test_meta_estimators_delegate_data_validation(estimator):
         y = rng.randint(3, size=n_samples)
 
     # We convert to lists to make sure it works on array-like
-    X = _enforce_estimator_tags_x(estimator, X).tolist()
+    X = _enforce_estimator_tags_X(estimator, X).tolist()
     y = _enforce_estimator_tags_y(estimator, y).tolist()
 
     # Calling fit should not raise any data validation exception since X is a