Simplify scaling of X dataframe

akaashp2000 · akaashp2000 · commit 9585d68d0f50 · 2023-11-03T21:33:03.000Z
diff --git a/sklearn/ensemble/tests/test_stacking.py b/sklearn/ensemble/tests/test_stacking.py
@@ -53,6 +53,8 @@
     n_classes=3, random_state=42
 )
 X_binary, y_binary = make_classification(n_classes=2, random_state=42)
+X_breast_cancer, y_breast_cancer = load_breast_cancer(return_X_y=True)
+X_breast_cancer = scale(X_breast_cancer)
 
 
 @pytest.mark.parametrize(
@@ -434,10 +436,8 @@ def test_stacking_classifier_stratify_default():
                 final_estimator=LogisticRegression(),
                 cv=KFold(shuffle=True, random_state=42),
             ),
-            *[
-                scale(data) if idx == 0 else data
-                for idx, data in list(enumerate(load_breast_cancer(return_X_y=True)))
-            ],
+            X_breast_cancer,
+            y_breast_cancer,
         ),
         (
             StackingRegressor(
@@ -500,10 +500,8 @@ def test_stacking_classifier_sample_weight_fit_param():
                 ],
                 final_estimator=LogisticRegression(),
             ),
-            *[
-                scale(data) if idx == 0 else data
-                for idx, data in list(enumerate(load_breast_cancer(return_X_y=True)))
-            ],
+            X_breast_cancer,
+            y_breast_cancer,
         ),
         (
             StackingRegressor(
