add a warning for the use of a classifier as ml_l

Author: SvenKlaassen

doubleml/plm/plr.py

@@ -120,6 +120,9 @@ def __init__(
         if ml_l_is_classifier:
             if obj_dml_data.binary_outcome:
                 self._predict_method = {"ml_g": "predict_proba"}
+                warnings.warn(
+                    f"The ml_l learner {str(ml_l)} was identified as classifier. Fitting an additive probability model."
+                )
             else:
                 raise ValueError(
                     f"The ml_l learner {str(ml_l)} was identified as classifier "

doubleml/plm/tests/test_plr_binary_outcome.py

@@ -54,7 +54,7 @@ def generate_binary_data():
 def test_dml_plr_binary_warnings(generate_binary_data, learner_binary, score):
     data = generate_binary_data
     obj_dml_data = dml.DoubleMLData(data, "y", ["d"])
-    msg = "The ml_l learner {str(ml_l)} was identified as classifier"
+    msg = "The ml_l learner .+ was identified as classifier. Fitting an additive probability model."
     with pytest.warns(UserWarning, match=msg):
         _ = dml.DoubleMLPLR(obj_dml_data, clone(learner_binary), clone(learner_binary), score=score)