关键词: 贝叶斯分类, 不完全朴素贝叶斯, 垃圾邮件

Abstract: Because Naive Bayes (NB) classification model is simple and effective, good efficiency can be achieved in antispam applications. On the other hand, the assumption of its attribute independence makes it unable to express its semantic dependence. This paper proposed a new antispam classification model based on semi-NB classification model, averaged on N one-dependence classification model. It relaxed the assumption of condition independence of each attribute. It was assumed that all attributes were dependent on one attribute (1-dependence). The average on N 1-dependence was regarded as the probability of each class label. This method is simple and efficient and decreases the classification error ratio.

Key words: Bayesian classification, semi-Naive Bayes, spam