Abstract: We are going to explore on how the elaboration of web results in all communication and transactions which are all taking place through web based tool known as email and these days all people are making all their general or business transactions through emails so email acts as an active machine for communication so the user essential time and amount of cash spent on bandwidth will be saved. Spam is an alternative way of an electronic messaging system to send a large number of messages to the user inbox. Here we are going to experiment many data mining techniques to the dataset of spam in an attempt to search the most suitable classifier to email classification as spam and non-spam. Here we are going to check the performance of many classifiers with the use of feature selection algorithm and we found that in the result analysis part the Na´ve Bayes classifier provides finer accuracy with respect to other two classifiers such as support vector machine and J48 and we can also see that time taken for Na´ve Bayes classifier is lesser than other two classifiers which means that Na´ve Bayes classifier is the best classifier among the other two classifier which are used for classifying the spam mails.
Keywords: Classifier, Feature selection, Emails, Spam mails.