Ejemplo n.º 1
0
def test_source_competence_rrc():
    rrc_test = RRC()
    rrc_test.n_classifiers_ = 1
    rrc_test.dsel_scores_ = np.array([[[0.3, 0.6, 0.1],
                                       [1.0 / 3, 1.0 / 3, 1.0 / 3],
                                       [0.5, 0.2, 0.3],
                                       [0.5, 0.2, 0.3]]]).reshape(4, 1, 3)
    rrc_test.DSEL_target_ = [1, 0, 0, 1]
    rrc_test.n_classes_ = 3
    rrc_test.n_samples_ = 4
    C_src = rrc_test.source_competence()
    expected = np.array([[0.7849], [0.3328], [0.6428], [0.1194]])
    assert np.allclose(C_src, expected, atol=0.01)
Ejemplo n.º 2
0
def test_source_competence_rrc():
    pool_classifiers = [
        create_base_classifier(return_value=1, return_prob=1.0)
    ]
    rrc_test = RRC(pool_classifiers=pool_classifiers)
    rrc_test.n_classifiers_ = len(pool_classifiers)
    rrc_test.dsel_scores_ = np.array(
        [[[0.3, 0.6, 0.1], [1.0 / 3, 1.0 / 3, 1.0 / 3], [0.5, 0.2, 0.3],
          [0.5, 0.2,
           0.3]]]).reshape(4, 1, 3)  # 4 samples, 1 classifier and 3 classes
    rrc_test.DSEL_target_ = [1, 0, 0, 1]
    rrc_test.n_classes_ = 3
    rrc_test.n_samples_ = 4
    C_src = rrc_test.source_competence()
    expected = np.array([[0.7849], [0.3328], [0.6428], [0.1194]])
    assert np.allclose(C_src, expected, atol=0.01)