def test_gnb_prior_large_bias():
 clf = GaussianNB(priors=np.array([0.01, 0.99]))
 clf.fit(X, y)
 assert_equal(clf.predict([[(-0.1), (-0.1)]]), np.array([2]))

def test_gnb_prior_large_bias ( ) : clf = GaussianNB ( priors = np . array ( [ 0.01 , 0.99 ] ) ) clf . fit ( X , y ) assert_equal ( clf . predict ( [ [ ( - 0.1 ) , ( - 0.1 ) ] ] ) , np . array ( [ 2 ] ) )
test if good prediction when class prior favor largely one class .