def test_FANN_converges_on_vote_problem(): fc = FullConnectionWithBias(9, 1) sig = SigmoidLayer(1) nn = FANN([fc, sig]) vote = generate_majority_vote() theta = np.zeros((10, )) for i in range(500): g = nn.calculate_gradient(theta, vote.data, vote.target) theta -= g * 1 error = nn.calculate_error(theta, vote.data, vote.target) assert_less(error, 0.2)
def test_FANN_converges_on_vote_problem(): fc = FullConnectionWithBias(9, 1) sig = SigmoidLayer(1) nn = FANN([fc, sig]) vote = generate_majority_vote() theta = np.zeros((10,)) for i in range(500): g = nn.calculate_gradient(theta, vote.data, vote.target) theta -= g * 1 error = nn.calculate_error(theta, vote.data, vote.target) assert_less(error, 0.2)
def test_generate_majority_vote_wellformed(): vote_problem = generate_majority_vote() assert_dataset_wellformed(vote_problem)