def test_standard():
y_targ = [0, 0, 0, 1, 1, 1]
y_pred = [0, 1, 1, 0, 1, 1]
y = accuracy_score(y_targ, y_pred, method='standard')
y_1 = accuracy_score(y_targ, y_pred, method='binary', normalize=False)
assert_almost_equal(y, float(3) / 6, decimal=4)
assert y_1 == 3
def test_multiclass_binary():
y_targ = [0, 0, 0, 1, 1, 1, 2, 2, 2]
y_pred = [1, 0, 0, 0, 1, 2, 0, 2, 2]
y_1 = accuracy_score(y_targ, y_pred, method='binary', pos_label=1)
y_2 = accuracy_score(y_targ, y_pred, method='binary', pos_label=2)
y_3 = accuracy_score(y_targ,
y_pred,
method='binary',
pos_label=1,
normalize=False)
assert_almost_equal(y_2, float(7) / 9, decimal=4)
assert_almost_equal(y_1, float(6) / 9, decimal=4)
assert y_3 == 6
def test_average():
y_targ = np.array([0, 0, 0, 1, 1, 1, 1, 1, 2, 2])
y_pred = np.array([0, 1, 1, 0, 1, 1, 2, 2, 2, 2])
y = accuracy_score(y_targ, y_pred, method='average')
assert_almost_equal(y, float(2) / 3, decimal=4)
def test_balanced_binary():
y_targ = np.array([0, 0, 0, 1, 1, 1, 1, 1, 1, 0])
y_pred = np.array([0, 1, 1, 0, 1, 1, 1, 1, 1, 1])
y = accuracy_score(y_targ, y_pred, method='balanced')
assert_almost_equal(y, 0.542, decimal=3)
def test_balanced_multiclass():
y_targ = np.array([0, 0, 0, 1, 1, 1, 1, 1, 2, 2])
y_pred = np.array([0, 1, 1, 0, 1, 1, 2, 2, 2, 2])
y = accuracy_score(y_targ, y_pred, method='balanced')
assert_almost_equal(y, 0.578, decimal=3)