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test_standard_datasets.py
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test_standard_datasets.py
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import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 50)
pd.set_option('display.max_columns', 10)
pd.set_option('display.width', 200)
from aif360.datasets import AdultDataset
from aif360.datasets import BankDataset
from aif360.datasets import CompasDataset
from aif360.datasets import GermanDataset
from aif360.metrics import BinaryLabelDatasetMetric
def test_compas():
# just test that there are no errors for default loading...
cd = CompasDataset()
# print(cd)
def test_german():
gd = GermanDataset()
bldm = BinaryLabelDatasetMetric(gd)
assert bldm.num_instances() == 1000
def test_adult_test_set():
ad = AdultDataset()
# test, train = ad.split([16281])
test, train = ad.split([15060])
assert np.any(test.labels)
def test_adult():
ad = AdultDataset()
# print(ad.feature_names)
assert np.isclose(ad.labels.mean(), 0.2478, atol=5e-5)
bldm = BinaryLabelDatasetMetric(ad)
assert bldm.num_instances() == 45222
def test_adult_no_drop():
ad = AdultDataset(protected_attribute_names=['sex'],
privileged_classes=[['Male']], categorical_features=[],
features_to_keep=['age', 'education-num'])
bldm = BinaryLabelDatasetMetric(ad)
assert bldm.num_instances() == 48842