div tzg

classifier/training.py

@@ -60,7 +60,7 @@ def train_single_thread(tid,p,le,key="answered"):
                 l=le.inverse_transform([ca])[0]
                 if type(l) is numpy.bool_:
                         l=bool(l)
-                if type(l) is numpy.string_:
+                if type(l) is numpy.string_ or type(l) is numpy.unicode_:
                         l=str(l)
                 store_training_data(tid,l, key)
         elif not ca.strip() == "":