Spam Mail Classifier
IJRASET Publication2022, International Journal for Research in Applied Science & Engineering Technology (IJRASET)
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Abstract
Email is the worldwide use of communication application. It is because of the ease of use and faster than other communication application. However, its inability to detect whether the mail content is either spam or ham degrade its performance. Nowadays, lot of cases have been reported regarding stealing of personal information or phishing activities via email from the user. This project will discuss how machine learning help in spam detection. Machine learning is an artificial intelligence application that provides the ability to automatically learn and improve data without being explicitly programmed. Binary classifier will be used to classify the text into two different categories: spam and ham. The algorithm will predict the score more accurately. The objective of developing this model is to detect and score word faster and accurately.
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1-4Student, Department of Computer Engineering, TEC, University of Mumbai, Mumbai, India 5Faculty, Department of Computer Engineering, TEC, University of Mumbai, Mumbai, India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract Due to its convenient, economical, fast, and easy to use nature Electronic mail is a vital revolution taking place over traditional communication systems. A main obstruction in electronic communications is the vast publicizing of unwanted, harmful emails known as spam emails. Lots of time of client is being wasted for sorting approaching mail and erasing undesirable correspondence, so there is a need for spam detection so that its outcomes can be reduced. The main aim is to development of suitable filters that can appropriately detect those emails and results in a high-performance rate.
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