def test_private_gaussian_mean(example_private_table: PrivateTable):
"""check private guassian mean implementation."""
noisy_mean = np.mean([
example_private_table.gaussian_mean('Age', PrivacyBudget(0.99, 0.5))
for i in range(100)
])
check_absolute_error(noisy_mean, 33.2, 10.)
def test_private_gaussian_mean_petal_length(example_private_table: PrivateTable):
"""check private gaussian mean implementation using Petal Length in iris dataset."""
noisy_mean = example_private_table.gaussian_mean('Petal Length', PrivacyBudget(0.99, 0.5))
check_absolute_error(noisy_mean, 3.7586666666666693, 1.)
def test_private_gaussian_mean(example_private_table: PrivateTable):
"""check private guassian mean implementation using Age in adult dataset."""
noisy_mean = example_private_table.gaussian_mean('Age',
PrivacyBudget(0.99, 0.5))
check_absolute_error(noisy_mean, 38.58164675532078, 1.)
def test_private_gaussian_mean_sepal_width(example_private_table: PrivateTable):
"""check private gaussian mean implementation using Sepal Width in iris dataset."""
noisy_mean = example_private_table.gaussian_mean('Sepal Width', PrivacyBudget(0.99, 0.5))
check_absolute_error(noisy_mean, 3.0540000000000007, 1.)
