Python l2_log_loss Exemples

Exemple #1

def test_l2_log_loss_with_observed():
    E = np.array([0, 1, 1])
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l2_log_loss(actual, predicted, E) == 0.0
    predicted = np.array([2, 1, 1])
    assert utils.l2_log_loss(actual, predicted, E) == 0.0

Exemple #2

Fichier : test_utils.py Projet : DGaffney/lifelines

def test_l2_log_loss_with_observed():
    E = np.array([0, 1, 1])
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l2_log_loss(actual, predicted, E) == 0.0
    predicted = np.array([2, 1, 1])
    assert utils.l2_log_loss(actual, predicted, E) == 0.0

Exemple #3

def test_l2_log_loss_with_no_observed():
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l2_log_loss(actual, predicted) == 0.0
    predicted = predicted + 1
    assert abs(utils.l2_log_loss(actual, predicted) - np.log(2) ** 2) < 10e-8

Exemple #4

Fichier : test_utils.py Projet : DGaffney/lifelines

def test_l2_log_loss_with_no_observed():
    actual = np.array([1, 1, 1])
    predicted = np.array([1, 1, 1])
    assert utils.l2_log_loss(actual, predicted) == 0.0
    predicted = predicted + 1
    assert abs(utils.l2_log_loss(actual, predicted) - np.log(2) ** 2) < 10e-8