Email Spam Detection Based on Exceptional Precision

Abstract

Email remains a crucial means of communication in personal and professional spheres; however, its efficiency is often compromised by the widespread presence of unwanted messages. The increase in unsolicited emails not only inundates email inboxes but also poses significant threats such as phishing, malware distribution, and financial fraud. To tackle these issues and enhance the effectiveness of email exchanges, there has been a notable emphasis on utilizing machine learning techniques for identifying spam. This paper will explore various machine learning algorithms and apply them to our datasets. The most optimal algorithm will be selected for email spam detection based on its exceptional precision and accuracy.