International Journal of Technology and Applied Science

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Email Spam Detection using Machine Learning Algorithms

Author(s) Setty Divyasree, Turpula Mythri, Doravari Khaja Modin, Bhukya Chayadevi, Dr M.C Bhanu Prasad
Country India
Abstract Email is the most effective form of communique in many organizations. Faces this method is utilized by spammers for fraudulent profit. Sending undesirable emails. The motive of this article is to give a method for detecting spam. Emails with superior system gaining knowledge of algorithms using biotechnology. An overview of the literature is carried out to explore the powerful strategies with the aid of which the routes are used. Clear other information to obtain higher results. A precise study has been finished Naive Bayes, system gaining knowledge of fashions gear using guide vector machines; Random Forest, Decision Tree and Multilayer Perceptron on Seven Different Emails datasets, and characteristic extraction and preprocessing. Life assist there were algorithms like particle optimization and genetic set of rules. To enhance the overall performance of carried out classifiers. Polynomial Naive Bayes Genetic algorithm shows better universal overall performance. A comparison of our outcomes. To provide a version well suited with different system gaining knowledge of and biotechnology models became additionally discussed.
Keywords cell computing devices, Email aid, junk mail detection.
Field Engineering
Published In Volume 17, Issue 4, April 2026
Published On 2026-04-05
Cite This Email Spam Detection using Machine Learning Algorithms - Setty Divyasree, Turpula Mythri, Doravari Khaja Modin, Bhukya Chayadevi, Dr M.C Bhanu Prasad - IJTAS Volume 17, Issue 4, April 2026.
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