统计垃圾邮件过滤器的有效性和局限性
Effectiveness and Limitations of Statistical Spam Filters
University of Kashmir（克什米尔大学）
摘要：
在本文中，我们讨论了著名的统计垃圾邮件过滤器的设计中涉及的技术，包括朴素贝叶斯，词频逆文档频率，K-最近邻，支持向量机，贝叶斯加性回归树。我们比较这些技术与对方的准确性，召回率，精度等。此外，我们讨论了统计过滤器在过滤出各种类型的垃圾邮件从合法的电子邮件的有效性和局限性。
英文摘要：
In this paper we discuss the techniques involved in the design of the famous statistical spam filters that include Naive Bayes, Term Frequency-Inverse Document Frequency, K-Nearest Neighbor, Support Vector Machine, and Bayes Additive Regression Tree. We compare these techniques with each other in terms of accuracy, recall, precision, etc. Further, we discuss the effectiveness and limitations of statistical filters in filtering out various types of spam from legitimate e-mails.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
