Comparision of Machine Learning and Deep Learning Methods for Spam Email Classification

Email is one of the most popular communication medium in today’s technology and is widely used by many people. How-ever, spam emails as become a significant problem in today’s society causing tremendous losses at individual as well as organizational level. Various email providers today are using different techniques to classify emails as spam or ham how-ever, spammers continue to develop new techniques to outsmart them. In this research paper, our agenda is to find out the most efficient algorithm for text-based spam emails that contain both the subject and contents of the email. Here, we also use different Pre-processing techniques on our email text before executing the algorithms so that they give greater accuracy. We also provide performance comparison between the various machine learning and deep learning techniques and measure them mainly on three factors i.e. Spam recall, Spam precision and Accuracy.