More informative error message for classification metrics given regression output (#9275)

jnothman · jmschrei · commit f99fd0dd2918 · 2017-07-10T08:31:10.000-07:00
diff --git a/sklearn/metrics/classification.py b/sklearn/metrics/classification.py
@@ -77,8 +77,8 @@ def _check_targets(y_true, y_pred):
         y_type = set(["multiclass"])
 
     if len(y_type) > 1:
-        raise ValueError("Can't handle mix of {0} and {1}"
-                         "".format(type_true, type_pred))
+        raise ValueError("Classification metrics can't handle a mix of {0} "
+                         "and {1} targets".format(type_true, type_pred))
 
     # We can't have more than one value on y_type => The set is no more needed
     y_type = y_type.pop()
diff --git a/sklearn/metrics/tests/test_classification.py b/sklearn/metrics/tests/test_classification.py
@@ -1344,7 +1344,8 @@ def test__check_targets():
             if type1 != type2:
                 assert_raise_message(
                     ValueError,
-                    "Can't handle mix of {0} and {1}".format(type1, type2),
+                    "Classification metrics can't handle a mix of {0} and {1} "
+                    "targets".format(type1, type2),
                     _check_targets, y1, y2)
 
             else:
diff --git a/sklearn/metrics/tests/test_common.py b/sklearn/metrics/tests/test_common.py
@@ -636,7 +636,8 @@ def test_inf_nan_input():
     for metric in CLASSIFICATION_METRICS.values():
         for y_true, y_score in invalids:
             assert_raise_message(ValueError,
-                                 "Can't handle mix of binary and continuous",
+                                 "Classification metrics can't handle a mix "
+                                 "of binary and continuous targets",
                                  metric, y_true, y_score)
 
 
