Implement a test for SVC probability estimates.

From: Fabian Pedregosa <fabian.pedregosa@inria.fr>

git-svn-id: https://scikit-learn.svn.sourceforge.net/svnroot/scikit-learn/trunk@660 22fbfee3-77ab-4535-9bad-27d1bd3bc7d8

scikits/learn/tests/test_svm.py

@@ -80,7 +80,10 @@ def test_probability():
     """
     clf = svm.SVC(probability=True)
     clf.fit(X, Y)
-    assert_array_almost_equal(clf.prob_predict(T), [])
+    assert_array_almost_equal(clf.prob_predict(T),
+                              [[ 0.81937173,  0.18062827],
+                               [ 0.18921888,  0.81078112],
+                               [ 0.2769648 ,  0.7230352 ]])
 
 
 def test_noncontiguous():