// single class variable
y = np.random.random_integers(1, 2, (nrows, 1))
t = Table(x, y)
learn = DummyLearner()
clf = learn(t)
clf.ret = Model.Value
y2 = clf(x, ret=Model.Probs)
After Change
// single class variable
y = np.random.random_integers(0, 1, (nrows, 1))
t = Table(Domain([DiscreteVariable("v" + str(i), values=np.unique(x[:, i]))
for i in range(ncols)],
DiscreteVariable("c", values=[1, 2])),
x, y)