diff --git a/scikits/learn/linear_model/logistic.py b/scikits/learn/linear_model/logistic.py
index e136eb69f70..822549b1c62 100644
--- a/scikits/learn/linear_model/logistic.py
+++ b/scikits/learn/linear_model/logistic.py
@@ -163,7 +163,7 @@ class LogisticRegression(BaseLibLinear, ClassifierMixin,
         _y = np.empty(y.shape)
         _y[np.where(y == classes[0])] = -1
         _y[np.where(y == classes[1])] = 1
-        _y.shape = (1, np.size(y))
+        _y = _y.reshape((1, -1))
 
         den = np.max(np.abs(np.dot(_y, X)))
         if den == 0.0:
diff --git a/scikits/learn/linear_model/sparse/logistic.py b/scikits/learn/linear_model/sparse/logistic.py
index 3a46b6fd20c..3a6717b3a75 100644
--- a/scikits/learn/linear_model/sparse/logistic.py
+++ b/scikits/learn/linear_model/sparse/logistic.py
@@ -154,7 +154,7 @@ class LogisticRegression(SparseBaseLibLinear, ClassifierMixin,
         _y = np.empty(y.shape)
         _y[np.where(y == classes[0])] = -1
         _y[np.where(y == classes[1])] = 1
-        _y.shape = (1, np.size(y))
+        _y = _y.reshape((1, -1))
 
         den = np.max(np.abs(_y * X))
         if den == 0.0: