REVIEW OF SOME MACHINE LEARNING ALGORITHMS FOR SPAM FILTERING

Nowadays spam emails are increasing dramatically and make problems to users. As we know, spam not only damage users’ profits, time consuming and band width, but also is has become as a risk to efficiency, reliability and security of network. In this article, we try to study some of the machine learning methods like SVM, Naïve Bayesian and Neural network applied to spam filtering and finally examine the measurement criteria (accuracy, recall, precision) of these three algorithms in terms of performance

کلیدواژه ها:

spam and ham emails ، spam detection ، spam filtering ، machine learning algorithms