Not allow None base estimator

Prokopios Gryllos · Prokopios Gryllos · commit 39e23c6bd298 · 2017-12-23T15:40:03.000+02:00
diff --git a/sklearn/calibration.py b/sklearn/calibration.py
@@ -24,6 +24,7 @@
 from .utils.fixes import signature
 from .isotonic import IsotonicRegression
 from .svm import LinearSVC
+from .linear_model import LogisticRegression
 from .model_selection import check_cv
 from .metrics.classification import _check_binary_probabilistic_predictions
 from .metrics.pairwise import euclidean_distances
@@ -87,7 +88,7 @@ class CutoffClassifier(BaseEstimator, ClassifierMixin):
         Decision threshold for the positive class. Determines the output of
         predict
     """
-    def __init__(self, base_estimator=None, method='roc', pos_label=1, cv=3,
+    def __init__(self, base_estimator, method='roc', pos_label=1, cv=3,
                  min_val_tnr=None, min_val_tpr=None):
         self.base_estimator = base_estimator
         self.method = method
@@ -112,15 +113,16 @@ def fit(self, X, y):
         self : object
             Instance of self.
         """
+        if not isinstance(self.base_estimator, BaseEstimator):
+            raise AttributeError('Base estimator must be of type BaseEstimator;'
+                                 'got %s instead' % type(self.base_estimator))
+
         X, y = check_X_y(X, y)
 
         self.label_encoder = LabelEncoder().fit(y)
         y = self.label_encoder.transform(y)
         self.pos_label = self.label_encoder.transform([self.pos_label])[0]
 
-        if not self.base_estimator:
-            self.base_estimator = LinearSVC(random_state=0)
-
         if self.cv == 'prefit':
             self.threshold = _CutoffClassifier(
                 self.base_estimator, self.method, self.pos_label,
