DOC give example of binarizing binary targets

jnothman · Hamzeh Alsalhi · commit eec979cb9b8e · 2014-06-24T21:17:05.000-04:00
H/T @ilam
diff --git a/sklearn/preprocessing/label.py b/sklearn/preprocessing/label.py
@@ -211,6 +211,14 @@ class LabelBinarizer(BaseEstimator, TransformerMixin):
     array([[1, 0, 0, 0],
            [0, 0, 0, 1]])
 
+    Binary targets transform to a column vector
+    >>> lb = preprocessing.LabelBinarizer()
+    >>> lb.fit_transform(['yes', 'no', 'no', 'yes'])
+    array([[1],
+           [0],
+           [0],
+           [1]])
+
     >>> import numpy as np
     >>> lb.fit(np.array([[0, 1, 1], [1, 0, 0]]))
     LabelBinarizer(neg_label=0, pos_label=1)
@@ -399,6 +407,14 @@ def label_binarize(y, classes, multilabel=False, neg_label=0, pos_label=1):
     array([[1, 0, 0, 0],
            [0, 1, 0, 0]])
 
+    Binary targets transform to a column vector
+
+    >>> label_binarize(['yes', 'no', 'no', 'yes'], classes=['no', 'yes'])
+    array([[1],
+           [0],
+           [0],
+           [1]])
+
     See also
     --------
     label_binarize : function to perform the transform operation of
