Spam Message Detection Using Logistic Regression


Authors : NIKHIL KUDUPUDI; SHILPA NAIR

Volume/Issue : Volume 6 - 2021, Issue 9 - September

Google Scholar : http://bitly.ws/gu88

Scribd : https://bit.ly/3AmSG6V

The use of the internet is increasing day by day, and the spammers who consistently try to spam people by sending fraud mails and SMS. Mails and SMS are one of the most important and most used means of communication, because of which 2.4 billion messages are sent every one second. With the rise of such exchange of emails and messages, some find it an opportunity to fill other's inbox with preposterous messages that reduce internet speed and plunders our personal data. However, due to recent advancements in technology, it is possible to find solutions to all such problems easily. With the help of Natural Language Processing and Machine Learning, we can quickly detect spam messages. One of the crucial aspects of research in the world of machine learning applications is "NLP". In this paper, we have proposed a model where emails would be classified into the categories of Spam or Ham.

Keywords : Spam-Detector, Natural Language Processing, Logistic Regression.

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