Fix minor errors

rsivapr · Sep 14, 2013 · 715ef0c · 715ef0c
1 parent 62fc931
commit 715ef0c
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Showing 2 changed files with 7 additions and 4 deletions.
diff --git a/sklearn/preprocessing/label.py b/sklearn/preprocessing/label.py
@@ -6,6 +6,8 @@
 
 import numpy as np
 
+from scipy.sparse import csc_matrix
+
 from ..base import BaseEstimator, TransformerMixin
 
 from ..utils.fixes import unique
@@ -396,7 +398,7 @@ def label_binarize(y, classes, multilabel=False, neg_label=0, pos_label=1):
             return y
         if neg_label != 0:
             # neg_label not zero eliminates possibility of a sparse matrix 
-            Y = np.zeros((len(y), len(classes)
+            Y = np.zeros((len(y), len(classes)), dtype=np.int)
             Y += neg_label
     else:
         Y = np.zeros((len(y), 1), dtype=np.int)
@@ -413,6 +415,7 @@ def label_binarize(y, classes, multilabel=False, neg_label=0, pos_label=1):
         imap = dict((v, k) for k, v in enumerate(classes))
 
         if neg_label == 0:
+            row, col, data = ([] for i in range(3))
             for i, label_tuple in enumerate(y):
                 for label in label_tuple:
                     row.append(i)

diff --git a/sklearn/utils/multiclass.py b/sklearn/utils/multiclass.py
@@ -146,10 +146,10 @@ def is_label_indicator_matrix(y):
     if not (hasattr(y, "shape") and y.ndim == 2 and y.shape[1] > 1):
         return False
     try:
-        n_labels = len(np.unique(y))
+        labels = np.unique(y)
     except TypeError:
-        n_labels = len(np.unique(y.data)) + 1
-    return n_labels <= 2 and (y.dtype.kind in 'biu'  # bool, int, uint
+        labels = np.setxor1d(y.data, [0])
+    return len(labels) <= 2 and (y.dtype.kind in 'biu'  # bool, int, uint
                                  or _is_integral_float(labels))