关键词: 垃圾邮件, 邮件过滤, 概率, 阈值, 分类决策

Abstract: This paper confers in depth to the limitations of the traditional Bayesian anti-spam mechanism. It seldom thinks about whether the threshold is suitable or not, so the recalling is reduced. Aiming at this question, the paper proposes a lower-error policy decision based on chance variable; and considering the particularity of email classification, a lower-risk policy decision based on chance variable is proposed. The experimental results show that the former one maybe a better way to classify the common text; and the latter one makes better performance on recalling and F value when dealing with emails, at the same time it keeps a lower risk of error judging.

Key words: spam email, email filter, probability, threshold, classify decision