def test_root_mean_square_error():
 y_real = np.array([0.0, 1.0, 0.0, 2.0, 3.0])
 y_pred = np.array([0.0, 1.0, 0.0, 2.0, 3.0])
 assert_equals(0.0, root_mean_square_error(y_real, y_pred))
 y_real = np.array([3.0, 1.0, 2.0, 1.0, 1.0])
 y_pred = np.array([0.0, 1.0, 0.0, 2.0, 3.0])
 assert_almost_equals(1.8973665961, root_mean_square_error(y_real, y_pred))

def test_root_mean_square_error ( ) : y_real = np . array ( [ 0.0 , 1.0 , 0.0 , 2.0 , 3.0 ] ) y_pred = np . array ( [ 0.0 , 1.0 , 0.0 , 2.0 , 3.0 ] ) assert_equals ( 0.0 , root_mean_square_error ( y_real , y_pred ) ) y_real = np . array ( [ 3.0 , 1.0 , 2.0 , 1.0 , 1.0 ] ) y_pred = np . array ( [ 0.0 , 1.0 , 0.0 , 2.0 , 3.0 ] ) assert_almost_equals ( 1.8973665961 , root_mean_square_error ( y_real , y_pred ) )
check that the metric root mean squared error .