提出了一种松弛方法,允许类别节点下的相邻子节点之间存在相关关系(有向边),这种方法称为树增强型简单贝叶斯分类器(tree augmented naive Bayes classifier,TAN)。实验结果表明,TAN比简单贝叶斯分类器(naive Bayes classifier,NBC)可以获得更高的分类精度。
On the basis of the study of naive Bayes classifiers (NBC), a new method- tree augmented naive Bayes classifier is proposed and applied to texture classification. The experiment results demonstrate that the new method performs better in overall classification precision than NBC.