cosmit

git-svn-id: https://scikit-learn.svn.sourceforge.net/svnroot/scikit-learn/trunk@453 22fbfee3-77ab-4535-9bad-27d1bd3bc7d8

scikits/learn/datasets/samples_generator/linear.py

@@ -18,9 +18,8 @@ def sparse_uncorrelated(nb_samples=100,nb_features=10):
 
     Returns
     -------
-    X : numpy array of shape (nb_samples,nb_features)
-	simulated samples.
-    Y : numpy array of shape (nb_samples)
+    X : numpy array of shape (nb_samples, nb_features) for input samples
+    Y : numpy array of shape (nb_samples) for labels
     """
     X = nr.normal(loc=0, scale=1, size=(nb_samples, nb_features))
     Y = nr.normal(loc=X[:, 2] + 2 * X[:, 3] - 2 * X[:,6] - 1.5 * X[:, 7],