贝叶斯网络以统计学为基础，是数据挖掘技术的一种方法。
On the base of statistics, the bayes network is a method of data mining.
特别是在当前数据较少或者较难获得的情况下，贝叶斯网络的这一优点更加明显。
Especially when the current data are scarce or hard to obtain, the advantage of the bayes network is evident.
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。
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.
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