In this work, we have reviewed the issue of spam mail which is a big problem in the area of Internet. The growing size of uncalled mass e-mail (or spam) has produced the requirement of a dependable anti-spam filter. Now a days the Machine learning (ML) proedures are being employed to spontaneously filter the spam e-mail in an effective manner. In this work, we have reviewed some of the prevalent ML approaches (such as Rough sets, Bayesian classification, SVMs, k-NN, ANNs and Artificial immune system) and of their use fullness in the issue of spam Email taxonomy. We have provided the depictions of the procedures and the divergence of their enactment on the basis of the quantity of Spam Assassin.
Spam e-mail, Machine learning Procedures and Filtering
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