CLN Create helper function

thomasjpfan · thomasjpfan · commit 7372ceeec6b5 · 2022-03-17T17:43:32.000-04:00
diff --git a/sklearn/multiclass.py b/sklearn/multiclass.py
@@ -102,6 +102,15 @@ def _predict_binary(estimator, X):
     return score
 
 
+def _threshold_for_binary_predict(estimator):
+    """Threshold for predictions from binary estimator."""
+    if hasattr(estimator, "decision_function") and is_classifier(estimator):
+        return 0.0
+    else:
+        # predict_proba threshold
+        return 0.5
+
+
 def _check_estimator(estimator):
     """Make sure that an estimator implements the necessary methods."""
     if not hasattr(estimator, "decision_function") and not hasattr(
@@ -426,12 +435,7 @@ def predict(self, X):
                 argmaxima[maxima == pred] = i
             return self.classes_[argmaxima]
         else:
-            if hasattr(self.estimators_[0], "decision_function") and is_classifier(
-                self.estimators_[0]
-            ):
-                thresh = 0
-            else:
-                thresh = 0.5
+            thresh = _threshold_for_binary_predict(self.estimators_[0])
             indices = array.array("i")
             indptr = array.array("i", [0])
             for e in self.estimators_:
@@ -770,13 +774,7 @@ def predict(self, X):
         """
         Y = self.decision_function(X)
         if self.n_classes_ == 2:
-            if hasattr(self.estimators_[0], "decision_function") and is_classifier(
-                self.estimators_[0]
-            ):
-                thresh = 0
-            else:
-                # predict_proba threshold
-                thresh = 0.5
+            thresh = _threshold_for_binary_predict(self.estimators_[0])
             return self.classes_[(Y > thresh).astype(int)]
         return self.classes_[Y.argmax(axis=1)]
 
