    def _calculate_f1_acc(true_positive, false_positive, false_negative, true_negative):
        if true_positive <= 0:
            return 0.0, 0.0, 0.0, 0.0

        precision = float(true_positive) / (true_positive + false_positive)
        recall = float(true_positive) / (true_positive + false_negative)
        f_1 = 2 * precision * recall / (precision + recall)
        accuracy = float(true_positive + true_negative) / \
            (true_positive + false_positive + false_negative + true_negative)

        return precision, recall, f_1, accuracy

    def print_confusion_matrix(self):
        """ 打印混淆矩阵 confusion matrix """
