South Asian Journal of Engineering and Technology

Vol. 8 No. 1 (2019): Volume 8, Supplementary Issue 1, Year 2019
Articles

CREDIT CARD FRAUD DETECTION USING BOOSTED STACKING

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  • Prabhakar E,
  • Naresh Kumar M,
  • Ponnar K,
  • Suresh A,
  • Jayandhiran R
Prabhakar E
Assistant Professor, Department of Computer Science and Engineering, Nandha College of Technology, Erode – 638 052, Tamil Nadu, India.
Naresh Kumar M
Student, Department of Computer Science and Engineering, Nandha College of Technology, Erode – 638 052, Tamilnadu, India.
Ponnar K
Student, Department of Computer Science and Engineering, Nandha College of Technology, Erode – 638 052, Tamil Nadu, India.
Suresh A
Student, Department of Computer Science and Engineering, Nandha College of Technology, Erode – 638 052, Tamilnadu, India.
Jayandhiran R
Student, Department of Computer Science and Engineering, Nandha College of Technology, Erode – 638 052, Tamilnadu, India.

Published 2019-04-06

Abstract

Credit card fraud is one of the severe issue in financial field. Huge amount of money is lost because of the credit card fraud. There are many studies related to credit card fraud detection. But most of the studies failed to analyse different set of attributes. This research concentrates on identifying the best machine learning algorithm for credit card fraud detection. Existing system used the hybrid methods. This method integrate AdaBoost and majority voting methods. But many of the existing system failed to obtain the higher level accuracy. In the proposed approach, combination of stacking and AdaBoost is considered. Model efficiency is calculated based on the accuracy. Results shows that the proposed approach provides better detection of credit card fraud.

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