Detection of Email Spam using Machine Learning Algorithms: A Comparative Study

In the digital world a lot of emails are received every day, and most of them are not of any relevance to us, some are containing suspicious links which can cause harm to our system in some way or other. This can be overcome by using spam detection. It is the process of classifying whether the email is a genuine one or if it is some kind of spam. The purpose of spam detection is to deliver relevant emails to the person and separate spam emails. Already every email service provider has spam detection but still, its accuracy is not that much, sometimes they classify useful emails as spam. This paper focuses on the comparative analysis approach, where various Machine Learning models are applied to the same dataset. The different machine learning models were compared based on accuracy and Precision. Support vector machine results in 98.09% accuracy.