%0 Journal Article %1 noauthororeditor %A Preeti, Anu | Ms. %D 2020 %J International Journal of Trend in Scientific Research and Development %K Filtering Machine Procedures Spam and email learning %N 6 %P 1160-1167 %T A Deep Analysis on Prevailing Spam Mail Filteration Machine Learning Approaches %U https://www.ijtsrd.com/computer-science/data-processing/33261/a-deep-analysis-on-prevailing-spam-mail-filteration-machine-learning-approaches/anu %V 4 %X 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. Anu | Ms. Preeti Ä Deep Analysis on Prevailing Spam Mail Filteration Machine Learning Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33261.pdf Paper Url: https://www.ijtsrd.com/computer-science/data-processing/33261/a-deep-analysis-on-prevailing-spam-mail-filteration-machine-learning-approaches/anu

@article{noauthororeditor, abstract = {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. Anu | Ms. Preeti "A Deep Analysis on Prevailing Spam Mail Filteration Machine Learning Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33261.pdf Paper Url: https://www.ijtsrd.com/computer-science/data-processing/33261/a-deep-analysis-on-prevailing-spam-mail-filteration-machine-learning-approaches/anu }, added-at = {2020-11-26T12:21:26.000+0100}, author = {Preeti, Anu | Ms.}, biburl = {https://www.bibsonomy.org/bibtex/25650a31297aaa4db681a276645b68fca/ijtsrd}, interhash = {4aae02b7266a38913c29364b752eeebe}, intrahash = {5650a31297aaa4db681a276645b68fca}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Filtering Machine Procedures Spam and email learning}, language = {English}, month = sep, number = 6, pages = {1160-1167}, timestamp = {2020-11-26T12:21:26.000+0100}, title = {A Deep Analysis on Prevailing Spam Mail Filteration Machine Learning Approaches }, url = {https://www.ijtsrd.com/computer-science/data-processing/33261/a-deep-analysis-on-prevailing-spam-mail-filteration-machine-learning-approaches/anu}, volume = 4, year = 2020 }