The study on the spam filtering technology based on Bayesian algorithm

This paper analyzed spam filtering technology, carried out a detailed study of Naive Bayes algorithm, and proposed the improved Naive Bayesian mail filtering technology. Improvement can be seen in text selection as well as feature extraction. The general Bayesian text classification algorithm mostly takes information gain and cross-entropy algorithm in feature selection. Through the principle of Bayesian analysis, it was found that the characteristics distribution is closely related to the ability of the feature representing class, so this paper proposes a new feature selection method based on class conditional distribution algorithm. Finally, the experiments show that the proposed algorithm can effectively filter spam.