• S.JancySickory Daisy

Web has turned into an unavoidable type of communication. Especially, E-mail has its own unavoidable spot in this present period. These E-mails are compromised by spontaneous messages called as spam messages. Spammers are the individuals who send these spam messages. As the focal points furnishes the disservices, these spam messages are to be anticipated. To stay away from these spam messages in inboxes, a few calculations have been presented. In light of these calculations, a few filtering techniques have been actualized. Usually, these filtering techniques, channels those spam messages and keep them from the inbox. Filtering techniques are partitioned by two: Machine learning and Non-Machine Learning. This paper gives a study about various algorithms for supervised machine learning techniques that are being used. In addition to that, their advantages and disadvantages are discussed elaborately

Spam mail filtering, Iterative Dichotomiser 3, Naives Bayes, Logistic Model Tree, Classification and Regression Tree,Multi Layer Perceptron

"Various Approaches of Machine learning and Non-Machine learning techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.46-50, May-2019, Available :http://www.jetir.org/papers/JETIRCI06009.pdf

"Various Approaches of Machine learning and Non-Machine learning techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp46-50, May-2019, Available at : http://www.jetir.org/papers/JETIRCI06009.pdf