Adding example for new_labels argument

mjbommar · mjbommar · commit ab788f75c8cf · 2014-06-08T15:52:36.000-04:00
diff --git a/doc/modules/preprocessing.rst b/doc/modules/preprocessing.rst
@@ -417,6 +417,20 @@ hashable and comparable) to numerical labels::
     >>> list(le.inverse_transform([2, 2, 1]))
     ['tokyo', 'tokyo', 'paris']
 
+By default, ``LabelEncoder`` will throw a ``ValueError`` in the event that
+labels are passed in ``transform`` that were not seen in ``fit``.  This
+behavior can be handled with the ``new_labels`` parameter, which supports
+``"raise"``, ``"nan"``, ``"update"``, and ``"label"`` strategies for
+handling new labels.  For example, the ``"label"`` strategy will assign
+the unseen values a label of ``-1``.
+
+    >>> le = preprocessing.LabelEncoder(new_labels="label")
+    >>> le.fit(["paris", "paris", "tokyo", "amsterdam"])
+    LabelEncoder(new_label_class=-1, new_labels='label')
+    >>> list(le.classes_)
+    ['amsterdam', 'paris', 'tokyo']
+    >>> le.transform(["tokyo", "tokyo", "paris", "rome"])
+    array([ 2,  2,  1, -1])
 
 Imputation of missing values
 ============================
