def test_reg_supervised_similar_clustering():
new_data, historical_data, column_names, target_name = generate_classification_data_and_models(
)
test_suite = structural_tests.StructuralData(new_data, historical_data,
column_names, target_name)
try:
absolute_distance = 2
test_suite.cls_supervised_similar_clustering(absolute_distance)
assert True
except:
assert False
def test_mutual_info_kmeans_scorer():
new_data, historical_data = generate_unsupervised_data()
columns = [
"similar_normal", "different_normal", "similar_gamma",
"different_gamma"
]
target = ''
test_suite = structural_tests.StructuralData(new_data, historical_data,
columns, target)
try:
min_similarity = 0.5
test_suite.mutual_info_kmeans_scorer(min_similarity)
assert True
except:
assert False