def test_matrix_measure_3(self): """ Test classification_model_performance_matrix. multiple classes case. """ observed = np.array([1, 0, 1, 0, 1, 0, 2, 3]) calculated = np.array([1, 0, 1, 1, 0, 2, 3, 0]) measure = evaluation.classification_model_performance_matrix(observed, calculated) expected_measure = np.array([[1, 1, 1, 0], [1, 2, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0]]) np.testing.assert_array_almost_equal(measure, expected_measure)
def test_matrix_measure_2(self): """ Test classification_model_performance_matrix. All correct case. """ observed = np.array([0, 1, 0, 1, 0, 0, 1]) calculated = np.array([0, 1, 1, 0, 0, 0, 1]) measure = evaluation.classification_model_performance_matrix(observed, calculated) expected_measure = np.array([[3, 1], [1, 2]]) np.testing.assert_array_almost_equal(measure, expected_measure)
def test_matrix_measure_2(self): """ Test classification_model_performance_matrix. All correct case. """ observed = np.array([0, 1, 0, 1, 0, 0, 1]) calculated = np.array([0, 1, 1, 0, 0, 0, 1]) measure = evaluation.classification_model_performance_matrix( observed, calculated) expected_measure = np.array([[3, 1], [1, 2]]) np.testing.assert_array_almost_equal(measure, expected_measure)
def test_matrix_measure_3(self): """ Test classification_model_performance_matrix. multiple classes case. """ observed = np.array([1, 0, 1, 0, 1, 0, 2, 3]) calculated = np.array([1, 0, 1, 1, 0, 2, 3, 0]) measure = evaluation.classification_model_performance_matrix( observed, calculated) expected_measure = np.array([[1, 1, 1, 0], [1, 2, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0]]) np.testing.assert_array_almost_equal(measure, expected_measure)