def test_check_pct_accuracy_value(pct_accuracy):
pool_classifiers = create_pool_classifiers()
with pytest.raises(ValueError):
desmi = DESMI(pool_classifiers, pct_accuracy=pct_accuracy)
desmi.fit(X_dsel_ex1, y_dsel_ex1)
def test_check_alpha_type(alpha):
pool_classifiers = create_pool_classifiers()
with pytest.raises(TypeError):
desmi = DESMI(pool_classifiers, alpha=alpha)
desmi.fit(X_dsel_ex1, y_dsel_ex1)
def test_mi(knn_methods):
pool_classifiers, X_dsel, y_dsel, X_test, y_test = setup_classifiers()
desmi = DESMI(pool_classifiers, alpha=0.9, knn_classifier=knn_methods)
desmi.fit(X_dsel, y_dsel)
assert np.isclose(desmi.score(X_test, y_test), 0.9787234042553191)
def test_mi():
pool_classifiers, X_dsel, y_dsel, X_test, y_test = setup_classifiers()
desmi = DESMI(pool_classifiers, alpha=0.9)
desmi.fit(X_dsel, y_dsel)
assert np.isclose(desmi.score(X_test, y_test), 0.3500000000)
def test_check_pct_accuracy_value(pct_accuracy, create_X_y):
X, y = create_X_y
with pytest.raises(ValueError):
desmi = DESMI(pct_accuracy=pct_accuracy)
desmi.fit(X, y)
def test_check_alpha_type(alpha, create_X_y):
X, y = create_X_y
with pytest.raises(TypeError):
desmi = DESMI(alpha=alpha)
desmi.fit(X, y)