Using Support Vector Machine For Classification And Feature Extraction Of Spam In Email

Abstract

We provide an overview of recent and successful content-based e-mail spam filtering algorithms in this article. Our main focus is on spam filters based on machine learning and variants influenced by them. We report on significant ideas, methodologies, key endeavors, and the field's current state-of-the-art. The initial interpretation of previous work demonstrates the fundamentals of spam filtering and feature engineering in e-mail. We finish by looking at approaches, procedures, and evaluation standards, as well as exploring intriguing offshoots of recent breakthroughs and proposing directions of future research.

Various Deep Learning Techniques Involved In Breast Cancer Mammogram Classification – A Survey

“…These innovative technologies make it possible to identify numerous, effective therapy alternatives for various patients (Ghantasala et al, 2021d). Machine learning models can employ deep neural networks to identify impending health issues or hazards and deliver particular medications or treatments with real-time data collecting from linked devices (Reddy et al, 2021).…”