Fixed NaN != NaN counting bug. (#100)

* Fixed NaN != NaN counting bug.

* Improved code.

Author: fealho

ctgan/transformer.py

@@ -50,13 +50,13 @@ def _fit_discrete(self, column, data):
         ohe = OneHotEncodingTransformer()
         data = data[:, 0]
         ohe.fit(data)
-        categories = len(set(data))
+        num_categories = len(ohe.dummies)
 
         return {
             'name': column,
             'encoder': ohe,
-            'output_info': [(categories, 'softmax')],
-            'output_dimensions': categories
+            'output_info': [(num_categories, 'softmax')],
+            'output_dimensions': num_categories
         }
 
     def fit(self, data, discrete_columns=tuple()):