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Spam Detection Using Machine Learning

  • Unique Paper ID: 164274
  • Volume: 10
  • Issue: 12
  • PageNo: 1347-1354
  • Abstract:
  • Email spam is a growing problem, causing frustration for users and posing risks to their security. To combat this issue, researchers have turned to machine learning techniques like Naive Bayes. This study compares Naive Bayes with other methods like Support Vector Machine (SVM) to see which is better at spotting spam. Using datasets of spam and legitimate emails, the researchers tested Naive Bayes and SVM. They found that while both methods were effective, SVM had slightly higher accuracy, with Naive Bayes close behind. The study also discusses the challenges of spam detection and the importance of machine learning in addressing this issue. By comparing different methods, it provides valuable insights into how we can better protect against email spam.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 1347-1354

Spam Detection Using Machine Learning

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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