메뉴 건너뛰기




Volumn 41, Issue 10, 2014, Pages 4915-4928

Learned lessons in credit card fraud detection from a practitioner perspective

Author keywords

Fraud detection; Incremental learning; Unbalanced data

Indexed keywords

LEARNING SYSTEMS; SIGNAL DETECTION;

EID: 84896514086     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2014.02.026     Document Type: Article
Times cited : (386)

References (55)
  • 1
    • 49549139345 scopus 로고
    • The area above the ordinal dominance graph and the area below the receiver operating characteristic graph
    • D. Bamber The area above the ordinal dominance graph and the area below the receiver operating characteristic graph Journal of Mathematical Psychology 12 1975 387 415
    • (1975) Journal of Mathematical Psychology , vol.12 , pp. 387-415
    • Bamber, D.1
  • 5
    • 0042421807 scopus 로고    scopus 로고
    • Statistical fraud detection: A review
    • R. Bolton, and D. Hand Statistical fraud detection: A review Statistical Science 2002 235 249
    • (2002) Statistical Science , pp. 235-249
    • Bolton, R.1    Hand, D.2
  • 12
    • 79952737601 scopus 로고    scopus 로고
    • Towards incremental learning of nonstationary imbalanced data stream: A multiple selectively recursive approach
    • S. Chen, and H. He Towards incremental learning of nonstationary imbalanced data stream: A multiple selectively recursive approach Evolving Systems 2 2011 35 50
    • (2011) Evolving Systems , vol.2 , pp. 35-50
    • Chen, S.1    He, H.2
  • 15
    • 34249966007 scopus 로고
    • The cn2 induction algorithm
    • P. Clark, and T. Niblett The cn2 induction algorithm Machine Learning 3 1989 261 283
    • (1989) Machine Learning , vol.3 , pp. 261-283
    • Clark, P.1    Niblett, T.2
  • 18
  • 19
    • 79961135005 scopus 로고    scopus 로고
    • R Development Core Team R Foundation for Statistical Computing, Vienna, Austria ISBN 3-900051-07-0
    • R Development Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, 2011. , ISBN 3-900051-07-0.
    • (2011) R: A Language and Environment for Statistical Computing
  • 22
    • 27344432474 scopus 로고    scopus 로고
    • C4. 5, class imbalance, and cost sensitivity: Why under-sampling beats over-sampling
    • Citeseer
    • C. Drummond, and R. Holte C4. 5, class imbalance, and cost sensitivity: Why under-sampling beats over-sampling Workshop on learning from imbalanced datasets II 2003 Citeseer
    • (2003) Workshop on Learning from Imbalanced Datasets II
    • Drummond, C.1    Holte, R.2
  • 24
    • 84864382523 scopus 로고    scopus 로고
    • Detection of rare items with target
    • G. Fan, and M. Zhu Detection of rare items with target Statistics and Its Interface 4 2011 11 17
    • (2011) Statistics and Its Interface , vol.4 , pp. 11-17
    • Fan, G.1    Zhu, M.2
  • 25
    • 84944811700 scopus 로고
    • The use of ranks to avoid the assumption of normality implicit in the analysis of variance
    • M. Friedman The use of ranks to avoid the assumption of normality implicit in the analysis of variance Journal of the American Statistical Association 32 1937 675 701
    • (1937) Journal of the American Statistical Association , vol.32 , pp. 675-701
    • Friedman, M.1
  • 26
    • 57049173376 scopus 로고    scopus 로고
    • Classifying data streams with skewed class distributions and concept drifts
    • J. Gao, B. Ding, W. Fan, J. Han, and P.S. Yu Classifying data streams with skewed class distributions and concept drifts Internet Computing 12 2008 37 49
    • (2008) Internet Computing , vol.12 , pp. 37-49
    • Gao, J.1    Ding, B.2    Fan, W.3    Han, J.4    Yu, P.S.5
  • 28
    • 40649128119 scopus 로고
    • Nonlinear neural networks: Principles, mechanisms, and architectures
    • S. Grossberg Nonlinear neural networks: Principles, mechanisms, and architectures Neural Networks 1 1988 17 61
    • (1988) Neural Networks , vol.1 , pp. 17-61
    • Grossberg, S.1
  • 29
    • 69549133517 scopus 로고    scopus 로고
    • Measuring classifier performance: A coherent alternative to the area under the ROC curve
    • D. Hand Measuring classifier performance: A coherent alternative to the area under the ROC curve Machine Learning 77 2009 103 123
    • (2009) Machine Learning , vol.77 , pp. 103-123
    • Hand, D.1
  • 30
    • 0003562954 scopus 로고    scopus 로고
    • A simple generalisation of the area under the ROC curve for multiple class classification problems
    • DOI 10.1023/A:1010920819831
    • D.J. Hand, and R.J. Till A simple generalisation of the area under the roc curve for multiple class classification problems Machine Learning 45 2001 171 186 (Pubitemid 33635984)
    • (2001) Machine Learning , vol.45 , Issue.2 , pp. 171-186
    • Hand, D.J.1    Till, R.J.2
  • 31
    • 84941476533 scopus 로고
    • Neue begründung der theorie quadratischer formen von unendlichvielen veränderlichen
    • E. Hellinger Neue begründung der theorie quadratischer formen von unendlichvielen veränderlichen Journal für die reine und Angewandte Mathematik 136 1909 210 271
    • (1909) Journal für Die Reine und Angewandte Mathematik , vol.136 , pp. 210-271
    • Hellinger, E.1
  • 33
    • 85011285088 scopus 로고    scopus 로고
    • Learning from streaming data with concept drift and imbalance: An overview
    • T.R. Hoens, R. Polikar, and N.V. Chawla Learning from streaming data with concept drift and imbalance: An overview Progress in Artificial Intelligence 1 2012 89 101
    • (2012) Progress in Artificial Intelligence , vol.1 , pp. 89-101
    • Hoens, T.R.1    Polikar, R.2    Chawla, N.V.3
  • 35
    • 33845536164 scopus 로고    scopus 로고
    • The class imbalance problem: A systematic study
    • N. Japkowicz, and S. Stephen The class imbalance problem: A systematic study Intelligent Data Analysis 6 2002 429 449
    • (2002) Intelligent Data Analysis , vol.6 , pp. 429-449
    • Japkowicz, N.1    Stephen, S.2
  • 37
    • 35048891979 scopus 로고    scopus 로고
    • Classifier ensembles for changing environments
    • Springer
    • L.I. Kuncheva Classifier ensembles for changing environments Multiple classifier systems 2004 Springer 1 15
    • (2004) Multiple Classifier Systems , pp. 1-15
    • Kuncheva, L.I.1
  • 38
    • 0345040873 scopus 로고    scopus 로고
    • Classification and regression by randomforest
    • A. Liaw, and M. Wiener Classification and regression by randomforest R News 2 2002 18 22
    • (2002) R News , vol.2 , pp. 18-22
    • Liaw, A.1    Wiener, M.2
  • 39
    • 77957058214 scopus 로고    scopus 로고
    • Adaptive methods for classification in arbitrarily imbalanced and drifting data streams
    • Springer
    • R.N. Lichtenwalter, and N.V. Chawla Adaptive methods for classification in arbitrarily imbalanced and drifting data streams New frontiers in applied data mining 2010 Springer 53 75
    • (2010) New Frontiers in Applied Data Mining , pp. 53-75
    • Lichtenwalter, R.N.1    Chawla, N.V.2
  • 46
    • 84896522400 scopus 로고    scopus 로고
    • The package implements different data-driven method for unbalanced datasets
    • unbalanced
    • Pozzolo, A. D. (2014). unbalanced: The package implements different data-driven method for unbalanced datasets. R package version 1.0.
    • (2014) R Package Version 1.0
    • Pozzolo, A.D.1
  • 48
    • 48749094245 scopus 로고    scopus 로고
    • Real-time credit card fraud detection using computational intelligence
    • J.T. Quah, and M. Sriganesh Real-time credit card fraud detection using computational intelligence Expert Systems with Applications 35 2008 1721 1732
    • (2008) Expert Systems with Applications , vol.35 , pp. 1721-1732
    • Quah, J.T.1    Sriganesh, M.2
  • 55
    • 0030126609 scopus 로고    scopus 로고
    • Learning in the presence of concept drift and hidden contexts
    • G. Widmer, and M. Kubat Learning in the presence of concept drift and hidden contexts Machine Learning 23 1996 69 101 (Pubitemid 126737384)
    • (1996) Machine Learning , vol.23 , Issue.1 , pp. 69-101
    • Widmer, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.