APPLICATION OF THE NAIVE BAYES METHOD IN SOLVING THE SPAM FILTERING PROBLEM

Abstract

Abstract. The relevance of the study on spam filtering lies in the fact that spam remains one of the biggest problems faced by the internet community. Currently, this problem has not been fully solved as new ways of organizing malicious or just unpleasant mailing are appearing.

In this work, one of the local methods of filtering, Bayesian filtering, has been considered. Bayesian filtering is a wide class of classification algorithms based on the principle of maximum a posteriori probability. The goal of the research is to assess the effectiveness of using Naive Bayes as a method of spam filtering. The expediency of the study lies in the fact that Naive Bayes is one of the most popular and affordable methods of spam filtering. This method is based on simple principles and allows you to effectively solve the problem of spam filtering using a minimum of resources. The practical significance of the study of this method lies in the fact that, compared with other classification algorithms, the Naive Bayes method has a high learning rate and can process a large number of functions.