Naïve Bayes Text Classifier

Haiyi Zhang, Di Li
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引用次数: 42

Abstract

Text classification algorithms, such SVM, and Naive Bayes, have been developed to build up search engines and construct spam email filters. As a simple yet powerful sample of Bayesian theorem, naive Bayes shows advantages in text classification yielding satisfactory results. In this paper, a spam email detector is developed using naive Bayes algorithm. We use pre-classified emails (priory knowledge) to train the spam email detector. With the model generated from the training step, the detector is able to decide whether an email is a spam email or an ordinary email.
Naïve贝叶斯文本分类器
文本分类算法,如支持向量机和朴素贝叶斯,已经发展到建立搜索引擎和构建垃圾邮件过滤器。朴素贝叶斯作为贝叶斯定理的一个简单而强大的例子,在文本分类中显示出了令人满意的结果。本文利用朴素贝叶斯算法开发了一种垃圾邮件检测系统。我们使用预先分类的电子邮件(先验知识)来训练垃圾邮件检测器。通过训练步骤生成的模型,检测器能够确定电子邮件是垃圾邮件还是普通电子邮件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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