def check_prediction(Xdf, y, yp, mean, std):
    """ Check the predicted classes and print results
    """
    ## MSE for testing
    total_error  = 0
    correct_class= 0

    y_pred_class = np.zeros((y.shape[2],))
    y_corr_pred_class = np.zeros((y.shape[2],))
    y_class      = np.zeros((y.shape[2],))
    y_labels = np.zeros((y.shape[1], y.shape[2]))
    a=['Buy','Sell','Hold']

    for i in range (y.shape[1]):
        delta = 0.
        for j in range(y.shape[2]):
            delta += (y[0][i][j] - yp[0][i][j]) * (y[0][i][j] - yp[0][i][j])