摘要： 机器学习算法在目前垃圾邮件过滤中扮演着重要的角色，但单一学习算法往往有各自的缺陷，限制了其在邮件过滤中的进一步应用。该文介绍了几种典型机器学习算法，并构造了一种基于多机器学习算法的投票式过滤模型。实验表明，该方法充分利用了各机器学习算法的优势，弥补了各自的不足，达到了比单一学习算法更好的过滤性能。

关键词: 垃圾邮件, 过滤, 机器学习, 投票

Abstract: The machine learning algorithms play an important role in current spam filter, but a single machine learning algorithm has its own drawback which restrains it from further application in E-mail filter. This paper introduces some typical machine learning algorithms, and constructs a voting E-mail filter model based on multi-machine learning algorithms. The experiments show that this method makes use of every machine learning algorithm’s advantage, and offsets its disadvantage, and achieves better filter performance than a single algorithm.

Key words: Spam, Filter, Machine learning, Voting