def test_feature_importances_feature_names(): feature_importances = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) feature_names = ['thing_a', 'thing_b', 'thing_c', 'thing_d', 'thing_e'] with open('static/table_ft_names.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(feature_importances, feature_names=feature_names))
def test_feature_importances_w_subestimators(): rf = Mock() tree_1 = Mock() tree_1.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) tree_2 = Mock() tree_2.feature_importances_ = np.array([0.10, 0.10, 0.8, 0.06, 0.01]) tree_3 = Mock() tree_3.feature_importances_ = np.array([0.09, 0.01, 0.9, 0.12, 0.02]) tree_4 = Mock() tree_4.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.01]) rf.estimators_ = [tree_1, tree_2, tree_3, tree_4] rf.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('tests/static/table_w_subestimator.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(rf))
def test_feature_importances_w_subestimators(): rf = Mock() tree_1 = Mock() tree_1.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) tree_2 = Mock() tree_2.feature_importances_ = np.array([0.10, 0.10, 0.8, 0.06, 0.01]) tree_3 = Mock() tree_3.feature_importances_ = np.array([0.09, 0.01, 0.9, 0.12, 0.02]) tree_4 = Mock() tree_4.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.01]) rf.estimators_ = [tree_1, tree_2, tree_3, tree_4] rf.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('static/table_w_subestimator.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(rf))
def test_feature_importances(self): with self.assertRaisesRegexp(ValueError, "needed to tabulate"): table.feature_importances(None)
def test_feature_importances(): model = Mock() model.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('tests/static/table.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(model))
def test_feature_importances_top3(): ft_imp = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('tests/static/table_top3.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(ft_imp, top_n=3))
def test_feature_importances_from_array(): feature_importances = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('tests/static/table.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(feature_importances))
def test_feature_importances_top3(): ft_imp = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('static/table_top3.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(ft_imp, top_n=3))
def test_feature_importances_from_array(): feature_importances = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('static/table.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(feature_importances))
def test_feature_importances(): model = Mock() model.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03]) with open('static/table.txt', 'r') as f: expected = f.read() assert expected == str(table.feature_importances(model))