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.
讨论了离散贝叶斯分类算法之后，推导了离散贝叶斯分类器的分类误差估算公式。
The algorithm of discrete Bayes classifier is proposed. Then, formulas for estimating classifying error of Bayes classifier are deduced.
文中提出了一种新的结构学习TANC - CBIC算法。并在贝叶斯分类器实验平台MBNC上编程实现。
This paper suggests a new structure-learning algorithm called TANC-CBIC, makes experiment in MBNC experiment platform with programming TANC-CBIC algorithm.
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