Handling scikit-learn's public vs. private API (part 1) (#1124)

yellowbrick/classifier/class_prediction_error.py

@@ -21,12 +21,17 @@
 import numpy as np
 
 from sklearn.utils.multiclass import unique_labels
-from sklearn.metrics._classification import _check_targets
 
 from yellowbrick.draw import bar_stack
 from yellowbrick.classifier.base import ClassificationScoreVisualizer
 from yellowbrick.exceptions import ModelError, YellowbrickValueError, NotFitted
 
+try:
+    # See #1124: this allows compatibility for scikit-learn >= 0.20
+    from sklearn.metrics._classification import _check_targets
+except ImportError:
+    from sklearn.metrics.classification import _check_targets
+
 
 ##########################################################################
 ## Class Prediction Error Chart