Understanding of the naive Bayes classifier in spam filtering
Qijia Wei · AIP conference proceedings · 2018
Along with the development of the Internet, the information stream is experiencing an unprecedented burst. The methods of information transmission become more and more important and people receiving effective information is a hot topic in the both research and industry field. As one of the most common methods of information communication, email has its own advantages. However, spams always flood the inbox and automatic filtering is needed. This paper is going to discuss this issue from the perspective of Naive Bayes Classifier, which is one of the applications of Bayes Theorem. Concepts and process of Naive Bayes Classifier will be introduced, followed by two examples. Discussion with Machine Learning is made in the last section. Naive Bayes Classifier has been proved to be surprisingly effective, with the limitation of the interdependence among attributes which are usually email words or phrases.