Automatic Filtering of Electronic Scam by Applying Naive Bayes Approach using Machine Learning

Authors

C Chamundeswari Devi, Mr C Balaji

Abstract

Email is a completely effective form of communique in many businesses. This approach is used by spammers to obtain fraudulent income by sending unwanted emails. The cause of this article is to indicate a way to come across junk mail. Letters with a lovely shape to advantage information about the mechanisms of the usage of biotechnology. An assessment of the literature is carried out to find powerful methods and numerous facts for exceptional results. A precise look conducted with Naive Bayes, the usage of vector machines; Random Forest, Decision Tree and multilayer perceptron on seven distinct e mail datasets, and feature extraction and preprocessing. Life is made easier through the use of techniques together with particle optimization and genetic programming. Improves the general overall performance of the implemented classifiers. Naive Bayesian multinomial genetic algorithm shows the pleasant of the overall performance. Further discussions were conducted to offer a more appropriate version for other structures of revel in acquisition and biotechnological modes.

Keywords

Email, Spammers, Biotechnology, Naive Bayes, Vector Machines, Random Forest, Decision Tree, Multilayer Perceptron, Easier, Overall Performance

Automatic Filtering of Electronic Scam by Applying Naive Bayes Approach using Machine Learning. C Chamundeswari Devi, Mr C Balaji. 2025. IJIRCT, Volume 11, Issue 2. Pages 1-6. https://www.ijirct.org/viewPaper.php?paperId=2504042