def test_sample_selection_working():
meta_test = METADES(
create_pool_all_agree(0, 10) + create_pool_all_agree(1, 5))
meta_test.processed_dsel = np.ones((5, 15))
meta_test.processed_dsel[(1, 3, 4), 5:] = 0
expected = np.asarray([1, 1 / 3, 1, 1 / 3, 1 / 3])
value = meta_test._sample_selection_agreement()
assert np.array_equal(value, expected)
def test_sample_selection_working():
meta_test = METADES()
meta_test.n_classifiers_ = 15
meta_test.DSEL_processed_ = np.ones((5, 15))
meta_test.DSEL_processed_[(1, 3, 4), 5:] = 0
expected = np.asarray([1, 1 / 3, 1, 1 / 3, 1 / 3])
value = meta_test._sample_selection_agreement()
assert np.array_equal(value, expected)
def test_sample_selection_working():
pool_classifiers = create_pool_all_agree(0, 10) + create_pool_all_agree(
1, 5)
meta_test = METADES(pool_classifiers=pool_classifiers)
meta_test.n_classifiers_ = len(pool_classifiers)
meta_test.DSEL_processed_ = np.ones((5, 15))
meta_test.DSEL_processed_[(1, 3, 4), 5:] = 0
expected = np.asarray([1, 1 / 3, 1, 1 / 3, 1 / 3])
value = meta_test._sample_selection_agreement()
assert np.array_equal(value, expected)
def test_sample_selection():
meta_test = METADES(
create_pool_all_agree(0, 10) + create_pool_all_agree(1, 5))
meta_test.processed_dsel = dsel_processed_ex1
value = meta_test._sample_selection_agreement(0)
assert value == 0.2
