In [13]: clf = svm.SVC(decision_function_shape='ovo', probability=True, gamma=0.0001, C=10000)

In [14]: clf.fit(X_train, Y_train)

In [28]: dec = clf.predict_proba(X_test)

In [29]: dec
Out[29]:
array([[ 0.08118061,  0.06775786,  0.10626706, ...,  0.05621558,
         0.1065483 ,  0.08721614],
       [ 0.45595692,  0.4307571 ,  0.00662802, ...,  0.01673492,
         0.01847479,  0.02867603],
       [ 0.45613055,  0.4464606 ,  0.00274494, ...,  0.02492393,
         0.01199296,  0.01798211],
       ...,
       [ 0.48795712,  0.41194125,  0.00385113, ...,  0.01506888,
         0.01728691,  0.01955625],
       [ 0.44479318,  0.46415402,  0.0179153 , ...,  0.02663468,
         0.00992754,  0.0051102 ],
       [ 0.49204286,  0.38378189,  0.00382213, ...,  0.03008399,
         0.02305889,  0.03207179]])

In [30]: dec.shape
Out[30]: (1000, 9)