propagate classes_ in metaestimators

Signed-off-by: Samuel Hoffman <hoffman.sc@gmail.com>

aif360/sklearn/postprocessing/__init__.py

@@ -27,6 +27,7 @@ class PostProcessingMeta(BaseEstimator, MetaEstimatorMixin):
     Attributes:
         estimator_: Fitted estimator.
         postprocessor_: Fitted postprocessor.
+        classes_ (array, shape (n_classes,)): Class labels from `estimator_`.
     """
 
     def __init__(self, estimator, postprocessor, *, prefit=False, val_size=0.25,
@@ -57,6 +58,11 @@ def __init__(self, estimator, postprocessor, *, prefit=False, val_size=0.25,
     def _estimator_type(self):
         return self.postprocessor._estimator_type
 
+    @property
+    def classes_(self):
+        """Class labels from the base estimator."""
+        return self.estimator_.classes_
+
     def fit(self, X, y, sample_weight=None, **fit_params):
         """Splits the training samples with
         :func:`~sklearn.model_selection.train_test_split` and uses the resultant

aif360/sklearn/preprocessing/reweighing.py

@@ -103,6 +103,7 @@ class ReweighingMeta(BaseEstimator, MetaEstimatorMixin):
     Attributes:
         estimator_ (sklearn.BaseEstimator): The fitted underlying estimator.
         reweigher_: The fitted underlying reweigher.
+        classes_ (array, shape (n_classes,)): Class labels from `estimator_`.
     """
     def __init__(self, estimator, reweigher=None):
         """
@@ -119,6 +120,11 @@ def __init__(self, estimator, reweigher=None):
     def _estimator_type(self):
         return self.estimator._estimator_type
 
+    @property
+    def classes_(self):
+        """Class labels from the base estimator."""
+        return self.estimator_.classes_
+
     def fit(self, X, y, sample_weight=None):
         """Performs ``self.reweigher_.fit_transform(X, y, sample_weight)`` and
         then ``self.estimator_.fit(X, y, sample_weight)`` using the reweighed