Sunday, 18 April 2021 14:41

Master Thesis in the Department of Computer Science discusses "Detecting Credit Card Fraud Using Machine Learning Algorithms"

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- The Department of Computer Science discussed the message tagged "Detecting Fraud on Credit Cards Using Machine Learning Algorithms" by student Nour Khaled Hussein Computer Science / General in the discussion room in the Department of Computer Science Building Wednesday 3/10/2021 The message, consisting of five chapters, aims to reduce and define The best data by using the approximate group theory to make the system more accurate and to address the time complexity and to test the ability of the proposed system to detect fraud in the credit card of different sizes of the data set, which leads to giving a detection and prediction system with the highest accuracy and the least processing time. This method focuses on proposing a method based on machine learning. The conclusions reached in this method are to use coarse group theory as a test for determining accuracy and time. This method was the best because it gave the best result according to accuracy and processing time, it was the best data set for sampling and the best result for time. The discussion committee consisted of:

  • Prof. Ahmed Tariq Sadiq as Chairman
  • Prof. Dr. Suhad Mal Allah as a member
  • Prof. Dr. Ikhlas Abbas Jabr as a member
  • Prof. Dr. Iyad Roudhan Abbas, member and supervisor
  • Dr. Bashar Saadoun Mahdi as a member and supervisor

 



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Source: Department's Media

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