International Journal on Science and Technology

E-ISSN: 2229-7677     Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.

SPAM EMAIL CLASSIFIER

Author(s) SATEESH RACHARLA, SANGATI NARENDRA REDDY, RAVULA RAJESH, DR.V.B.GANAPATHY
Country India
Abstract E-mail stands as a highly common communication medium because users can reach anywhere in the world at a reasonable price point and experience speedy message delivery.This is where E-mail spam/ham detection comes into the play,playing a significant role in classifying the emails into spam or ham respectively and thus saving users a lot of time to fetch their E-mails. Spam prevention approaches developed thus far but filtering proves to be the most essential method for stopping spam.technique.So today almost everyone around the globe is using emails with various purposes and hence an efficient growth in the no.of spam emails is witnessed with their genuine/ham emails because of which their precious time is wasted and the system becomes less efficient. The research explores the effectiveness of proposed work through identifying its application methods.This research paper aims to apply the Machine Learning Algorithm i.e. multinomial Naive bayes classifier to classify E-mails into spam or ham.The majority of academic studies focusing on spam filtering deal with advanced classifier-related aspects. In recent days, Machine Spam classification by means of machine learning stands as an essential research topic.
The majority of academic studies focusing on spam filtering deal with advanced classifier-related aspects. In recent days, Machine Spam classification by means of machine learning stands as an essential research topic. The research explores the effectiveness of proposed work through identifying its application methods.The research investigates various learning algorithms which detect spam e-mails from the email system. A study comparing different algorithms exists in the document presented.
Keywords Machine Learning,Spam Classification,Naive Bayesian,Feature Subset Selection,Face recognition,voice command
Field Engineering
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-03-28
Cite This SPAM EMAIL CLASSIFIER - SATEESH RACHARLA, SANGATI NARENDRA REDDY, RAVULA RAJESH, DR.V.B.GANAPATHY - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.3025
DOI https://doi.org/10.71097/IJSAT.v16.i1.3025
Short DOI https://doi.org/g896dv

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