用于电子邮件的反垃圾邮件过滤的堆叠分类器
Stacking classifiers for anti-spam filtering of e-mail
摘要：
我们评估经验相结合的分类器，被称为堆叠泛化，在反垃圾邮件过滤，一种新的成本敏感的文本分类应用程序的背景下，计划。未经请求的商业电子邮件或“垃圾邮件”充斥邮箱，造成挫折，浪费带宽，并使未成年人接触到不合适的内容。使用公共语料库，我们表明，堆叠可以提高自动诱导的反垃圾邮件过滤器的效率，这样的过滤器可以在现实生活中的应用。
英文摘要：
We evaluate empirically a scheme for combining classifiers, known as stacked generalization, in the context of anti-spam filtering, a novel cost-sensitive application of text categorization. Unsolicited commercial e-mail, or "spam", floods mailboxes, causing frustration, wasting bandwidth, and exposing minors to unsuitable content. Using a public corpus, we show that stacking can improve the efficiency of automatically induced anti-spam filters, and that such filters can be used in real-life applications.
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。
