Python l1_log_loss Examples

Example #1

def test_l1_log_loss_with_observed():
    E = np.array([0, 1, 1])
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l1_log_loss(actual, predicted, E) == 0.0
    predicted = np.array([2, 1, 1])
    assert utils.l1_log_loss(actual, predicted, E) == 0.0

Example #2

File: test_utils.py Project: DGaffney/lifelines

def test_l1_log_loss_with_observed():
    E = np.array([0, 1, 1])
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l1_log_loss(actual, predicted, E) == 0.0
    predicted = np.array([2, 1, 1])
    assert utils.l1_log_loss(actual, predicted, E) == 0.0

Example #3

def test_l1_log_loss_with_no_observed():
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l1_log_loss(actual, predicted) == 0.0
    predicted = predicted + 1
    assert utils.l1_log_loss(actual, predicted) == np.log(2)

Example #4

File: test_utils.py Project: DGaffney/lifelines

def test_l1_log_loss_with_no_observed():
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l1_log_loss(actual, predicted) == 0.0
    predicted = predicted + 1
    assert utils.l1_log_loss(actual, predicted) == np.log(2)