Email Spam Detection Using Logistic Regression


  • Manu Garg , Parveen , Muskan Gupta , Ojasvi



More dependable and powerful anti-spam filters were urgently needed as the quantity of spam, or unwanted email, increased. Spam emails are detected and filtered effectively using contemporary machine learning techniques. We give a thorough analysis of a few well-liked machine learning-based spam filter systems. Our study provides a summary of key theories, experiments, results, and future directions for spam filtering work. In the study's backdrop, an initial study looks at how machine learning techniques are used by top Internet service providers (ISPs) including Gmail and Yahoo junk mail filters to filter email spam. Discussion of the overall spam filtering process shows that several researchers have tried to use machine learning approaches to reduce spam. In this analysis, we contrast the pros and cons of current machine learning for solving spam filtering issues. Keywords – Machine Learning, E-mails, Spam Filtering, research.



2022-12-31 — Updated on 2022-12-31

How to Cite

Manu Garg , Parveen , Muskan Gupta , Ojasvi. (2022). Email Spam Detection Using Logistic Regression. Journal of Pharmaceutical Negative Results, 2111–2118.