Spam Filtering: A Comparison Between Different Machine Learning Classifiers

$E$-mail has become an integral part of day-to-day life. It has become one of the important and convenient forms of communication for both professional as well as personal use. This type of communication saves a lot of time of human beings. Emails can be considered as either spam or ham. Spam has become one of the major problems to internet users. It is very important to get rid of spam mails. Generally, users do not have much control over the accessing of mails and have to accept whatever that comes in to their inbox. Many spam filtering techniques has been introduced to overcome the problems caused by spam. In this paper, a comparison between different machine learning classifiers used for spam classification is presented.