Feature extraction and classification of spam emails

Muhammad Ali Hassan, Nhamo Mtetwa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)
1247 Downloads (Pure)


Emails are a popular and preferred way of written communication in our daily life. The problem with emails is spam. These spam emails are sent with different intentions, but advertisement and fraud are the main reasons. As being inexpensive to send, it causes many problems to the internet society. This paper discusses the use of different feature extraction methods coupled with two different supervised machine learning classifiers evaluated using four performance metrics on two publicly available spam email datasets for spam filtering. We highlight the importance of the correct coupling of feature extraction and classifier, and the merits of using two independent datasets.
Original languageEnglish
Title of host publication2018 5th International Conference on Soft Computing & Machine Intelligence (ISCMI)
Number of pages6
ISBN (Electronic)9781728113012
Publication statusPublished - 2 May 2019

Publication series

ISSN (Print)2640-0154
ISSN (Electronic)2640-0146


  • spam emails
  • machine intelligence
  • computing
  • Naïve Bayes
  • support vector machine
  • machine learning
  • spam feature extraction

ASJC Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications


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