diff --git a/apt/minimization/minimizer.py b/apt/minimization/minimizer.py
index 8f2d1b8..f0d2840 100644
--- a/apt/minimization/minimizer.py
+++ b/apt/minimization/minimizer.py
@@ -102,7 +102,7 @@ class GeneralizeToRepresentative(BaseEstimator, MetaEstimatorMixin, TransformerM
         self.features_to_minimize = features_to_minimize
         self.feature_slices = feature_slices
         if self.feature_slices:
-            self.all_one_hot_features = set([str(feature) for encoded in self.feature_slices for feature in encoded])
+            self.all_one_hot_features = {str(feature) for encoded in self.feature_slices for feature in encoded}
         else:
             self.all_one_hot_features = set()
         self.train_only_features_to_minimize = train_only_features_to_minimize
@@ -398,6 +398,14 @@ class GeneralizeToRepresentative(BaseEstimator, MetaEstimatorMixin, TransformerM
             self._ncp_scores.generalizations_score = self.calculate_ncp(x_test_dataset)
         else:
             print('No fitting was performed as some information was missing')
+            if not self.estimator:
+                print('No estimator provided')
+            elif not dataset:
+                print('No data provided')
+            elif dataset.get_samples() is None:
+                print('No samples provided')
+            elif dataset.get_labels() is None:
+                print('No labels provided')
 
         # Return the transformer
         return self
@@ -736,6 +744,8 @@ class GeneralizeToRepresentative(BaseEstimator, MetaEstimatorMixin, TransformerM
                             feature_value = 0
                         elif range['end'] is None and range['start'] > 0:
                             feature_value = 1
+                        else:
+                            raise ValueError('Illegal range for 1-hot encoded feature')
                         new_cell['categories'][feature] = [feature_value]
 
                         # need to add other columns that represent same 1-hot encoded feature
@@ -1279,7 +1289,7 @@ class GeneralizeToRepresentative(BaseEstimator, MetaEstimatorMixin, TransformerM
     def _get_other_features_in_encoding(feature, feature_slices):
         for encoded in feature_slices:
             if feature in encoded:
-                return (list(set(encoded) - set([feature]))), encoded
+                return (list(set(encoded) - {feature})), encoded
         return [], []
 
     @staticmethod