scikit-learn
diff --git a/‎sklearn/utils/estimator_checks.py
Lines changed: 21 additions & 28 deletions b/‎sklearn/utils/estimator_checks.py
Lines changed: 21 additions & 28 deletions
@@ -4070,37 +4070,30 @@ def check_param_validation(name, estimator_orig):
             f"parameter {param_name} does not have a valid type or value."
         )
 
-        # If the parameter constraint equals object, the bad parameter
-        # doesn't raise an appropriate exception. Object is a placeholder
-        # for all kinds of types, that can't be tested properly at the
-        # moment, e.g. numpy data types
-        # TODO: Remove this, if all data types can be validated correctly
-        if estimator_orig._parameter_constraints[param_name] != [object]:
-
-            estimator = clone(estimator_orig)
+        estimator = clone(estimator_orig)
 
-            # First, check that the error is raised if param doesn't match any valid
-            # type.
-            estimator.set_params(**{param_name: param_with_bad_type})
+        # First, check that the error is raised if param doesn't match any valid
+        # type.
+        estimator.set_params(**{param_name: param_with_bad_type})
 
-            for method in methods:
-                with raises(ValueError, match=match, err_msg=err_msg):
-                    getattr(estimator, method)(X, y)
+        for method in methods:
+            with raises(ValueError, match=match, err_msg=err_msg):
+                getattr(estimator, method)(X, y)
 
-            # Then, for constraints that are more than a type constraint, check that
-            # the error is raised if param does match a valid type but does not match
-            # any valid value for this type.
-            constraints = estimator_orig._parameter_constraints[param_name]
-            constraints = [make_constraint(constraint) for constraint in constraints]
+        # Then, for constraints that are more than a type constraint, check that
+        # the error is raised if param does match a valid type but does not match
+        # any valid value for this type.
+        constraints = estimator_orig._parameter_constraints[param_name]
+        constraints = [make_constraint(constraint) for constraint in constraints]
 
-            for constraint in constraints:
-                try:
-                    bad_value = generate_invalid_param_val(constraint, constraints)
-                except NotImplementedError:
-                    continue
+        for constraint in constraints:
+            try:
+                bad_value = generate_invalid_param_val(constraint, constraints)
+            except NotImplementedError:
+                continue
 
-                estimator.set_params(**{param_name: bad_value})
+            estimator.set_params(**{param_name: bad_value})
 
-                for method in methods:
-                    with raises(ValueError, match=match, err_msg=err_msg):
-                        getattr(estimator, method)(X, y)
+            for method in methods:
+                with raises(ValueError, match=match, err_msg=err_msg):
+                    getattr(estimator, method)(X, y)