In order to solve the problem existing in training data sets, present Bayes algorithm is im - proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.
为了解决该方法存在的训练数据集问题,本文改进了现有的贝叶斯分类算法,提出了利用未标记数据提高贝叶斯分类器性能的方法。
It is shown that the proposed algorithm has the virtues of strong anti-jamming capability and high precise.
实验表明,该自动提取算法具有一定的抗干扰能力和较好的检测精度。
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