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Spam Detection Using Machine Learning
2020
Computer Engineering and Intelligent Systems
Emails are essential in present century communication however spam emails have contributed negatively to the success of such communication. Studies have been conducted to classify messages in an effort to distinguish between ham and spam email by building an efficient and sensitive classification model with high accuracy and low false positive rate. Regular rule-based classifiers have been overwhelmed and less effective by the geometric growth in spam messages, hence the need to develop a more
doi:10.7176/ceis/11-3-04
fatcat:nfyzhh23ubfhzoewyuvqwh6ka4