한국지능시스템학회논문지 (Journal of the Korean Institute of Intelligent Systems)

  • 제11권5호
  • /
  • Pages.400-405
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  • 2001
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  • 1976-9172(pISSN)
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  • 2288-2324(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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신용카드 사기 검출을 위한 신경망 분류기의 진화 학습

Evolutionary Learning of Neural Networks Classifiers for Credit Card Fraud Detection

  • 박래정 (강릉대학교 정보전자공학부)
  • 발행 : 2001.10.01
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초록

This paper addresses an effective approach of training neural networks classifiers for credit card fraud detection. The proposed approach uses evolutionary programming to trails the neural networks classifiers based on maximization of the detection rate of fraudulent usages on some ranges of the rejection rate, loot minimization of mean square error(MSE) that Is a common criterion for neural networks learning. This approach enables us to get classifier of satisfactory performance and to offer a directive method of handling various conditions and performance measures that are required for real fraud detection applications in the classifier training step. The experimental results on "real"credit card transaction data indicate that the proposed classifiers produces classifiers of high quality in terms of a relative profit as well as detection rate and efficiency.

키워드

참고문헌

  1. Data Mining and Knowledge Discovery v.1 no.1 Adaptive fraud detection T. Fawcett;F. Provost
  2. IEEE Trans. on Neural Networks v.8 no.4 Neural fraud detection in credit card operations J. R. Dorronsoro;F. Ginel;C. Sanchez;C. S. Cruz
  3. Proc. of the Korea-U.S. Science and Technology Symposium A credit card fraud detection system based on hybrid of neural networks and decision tree L.-J. Park;S.-A. Kim;H.-J. Cho;T.-S. Kim;B.-H. Wang
  4. Proc. of Int'l Conf. Knowledge Discovery and Data Mining Toward scalable learning with non-uniform class and cost distributions : A case study in credit card fraud detection P. K. Chan;S. J. Stolfo
  5. KDD-98 Workshop on Distributed Data Mining Learning with non-uniform class and cost distributions : Effects and a distributed multi-classifier approach P. K. Chan;S. J. Stolfo
  6. IEEE Intelligent Systems v.14 no.6 Distributed data mining in credit card fraud detection P. K. Chan;W. Fan;A. L. Prodromidis;S. J. Stolfo
  7. AAAI'2000 Workshop on Imbalanced Data Sets Learning with imbalanced data sets 101 F. Provost
  8. Proc. of Int'l Conf. Knowledge Discovery and Data Mining Analysis and visualization of classifier performance : Comparision under imprecise class and cost distributions F. Provost;T. Fawcett
  9. Pattern Classification and Scene Analysis R. O. Duda;P. E. Hart
  10. Handbook of Evolutionary Computation T B$\"{a}$ck;D. B. Fogel;Z. Michalewicz
  11. Proceedings of the IEEE v.87 no.9 Evolving artificial neural networks X. Yao