MNT Use regression data for check_sample_weight_invariance test on …

…multioutput regression metrics (scikit-learn#30829)
yuvipanda · Feb 14, 2025 · ebc1276 · ebc1276
1 parent 2b97ac5
commit ebc1276
Showing 1 changed file with 14 additions and 1 deletion.
diff --git a/sklearn/metrics/tests/test_common.py b/sklearn/metrics/tests/test_common.py
@@ -1611,7 +1611,7 @@ def test_multiclass_sample_weight_invariance(name):
 @pytest.mark.parametrize(
     "name",
     sorted(
-        (MULTILABELS_METRICS | THRESHOLDED_MULTILABEL_METRICS | MULTIOUTPUT_METRICS)
+        (MULTILABELS_METRICS | THRESHOLDED_MULTILABEL_METRICS)
         - METRICS_WITHOUT_SAMPLE_WEIGHT
     ),
 )
@@ -1638,6 +1638,19 @@ def test_multilabel_sample_weight_invariance(name):
         check_sample_weight_invariance(name, metric, y_true, y_pred)
 
 
+@pytest.mark.parametrize(
+    "name",
+    sorted(MULTIOUTPUT_METRICS - METRICS_WITHOUT_SAMPLE_WEIGHT),
+)
+def test_multioutput_sample_weight_invariance(name):
+    random_state = check_random_state(0)
+    y_true = random_state.uniform(0, 2, size=(20, 5))
+    y_pred = random_state.uniform(0, 2, size=(20, 5))
+
+    metric = ALL_METRICS[name]
+    check_sample_weight_invariance(name, metric, y_true, y_pred)
+
+
 def test_no_averaging_labels():
     # test labels argument when not using averaging
     # in multi-class and multi-label cases