메뉴 건너뛰기




Volumn 28, Issue 1, 2012, Pages 224-238

Instance sampling in credit scoring: An empirical study of sample size and balancing

Author keywords

Balancing; Credit scoring; Data pre processing; Over sampling; Sample size; Under sampling

Indexed keywords


EID: 84155194931     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2011.07.006     Document Type: Article
Times cited : (147)

References (54)
  • 2
    • 0031521799 scopus 로고    scopus 로고
    • Analyzing credit risk data: a comparison of logistic discrimination, classification tree analysis, and feedforward networks
    • Arminger G., Enache D., Bonne T. Analyzing credit risk data: a comparison of logistic discrimination, classification tree analysis, and feedforward networks. Computational Statistics 1997, 12(2):293-310.
    • (1997) Computational Statistics , vol.12 , Issue.2 , pp. 293-310
    • Arminger, G.1    Enache, D.2    Bonne, T.3
  • 4
    • 34447098980 scopus 로고    scopus 로고
    • Reject inference, augmentation, and sample selection
    • Banasik J., Crook J. Reject inference, augmentation, and sample selection. European Journal of Operational Research 2007, 183(3):1582-1594.
    • (2007) European Journal of Operational Research , vol.183 , Issue.3 , pp. 1582-1594
    • Banasik, J.1    Crook, J.2
  • 6
    • 84155188638 scopus 로고    scopus 로고
    • Barclay's Barlcay's annual report 2008. (accessed on 9.12.09).
    • Barclay's (2008). Barlcay's annual report 2008. (accessed on 9.12.09). http://www.barclaysannualreport.com/ar2008/files/pdf/Annual_Report_2008.pdf.
    • (2008)
  • 7
    • 0004536889 scopus 로고
    • Methods applied to slow payers
    • Clarendon Press, Oxford, L.C. Thomas, J.N. Crook, D.B. Edelman (Eds.)
    • Boyle M., Crook J.N., Hamilton R., Thomas L.C. Methods applied to slow payers. Credit scoring and credit control 1992, Clarendon Press, Oxford. L.C. Thomas, J.N. Crook, D.B. Edelman (Eds.).
    • (1992) Credit scoring and credit control
    • Boyle, M.1    Crook, J.N.2    Hamilton, R.3    Thomas, L.C.4
  • 8
    • 84155188636 scopus 로고    scopus 로고
    • C4.5 and imbalanced datasets: investigating the effect of sampling method, probabilistic estimate, and decision tree structure. In Proceedings of the ICML'03 workshop on class imbalances.
    • Chawla, N. V. (2003). C4.5 and imbalanced datasets: investigating the effect of sampling method, probabilistic estimate, and decision tree structure. In Proceedings of the ICML'03 workshop on class imbalances.
    • (2003)
    • Chawla, N.V.1
  • 10
    • 27144549260 scopus 로고    scopus 로고
    • Special issue on learning from imbalanced data sets
    • guest editors
    • Chawla N.V., Japkowicz N., Kolcz A. Special issue on learning from imbalanced data sets. ACM SIGKDD: Explorations 2004, 6(1). guest editors.
    • (2004) ACM SIGKDD: Explorations , vol.6 , Issue.1
    • Chawla, N.V.1    Japkowicz, N.2    Kolcz, A.3
  • 11
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • Cohn D., Atlas L., Ladner R. Improving generalization with active learning. Machine Learning 1994, 15(2):201-221.
    • (1994) Machine Learning , vol.15 , Issue.2 , pp. 201-221
    • Cohn, D.1    Atlas, L.2    Ladner, R.3
  • 12
    • 33744976067 scopus 로고    scopus 로고
    • The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing
    • Crone S.F., Lessmann S., Stahlbock R. The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing. European Journal of Operational Research 2006, 173(3):781-800.
    • (2006) European Journal of Operational Research , vol.173 , Issue.3 , pp. 781-800
    • Crone, S.F.1    Lessmann, S.2    Stahlbock, R.3
  • 15
    • 84155180513 scopus 로고    scopus 로고
    • C4.5, class imbalance, and cost sensitivity: Why under-sampling beats over-sampling. In Proceedings of the ICML'03 workshop on learning from imbalanced data sets.
    • Drummond, C., & Holte, R. (2003). C4.5, class imbalance, and cost sensitivity: Why under-sampling beats over-sampling. In Proceedings of the ICML'03 workshop on learning from imbalanced data sets.
    • (2003)
    • Drummond, C.1    Holte, R.2
  • 17
    • 33745770046 scopus 로고    scopus 로고
    • Predictive models of expenditure and indebtedness for assessing the affordability of new consumer credit applications
    • Finlay S.M. Predictive models of expenditure and indebtedness for assessing the affordability of new consumer credit applications. Journal of the Operational Research Society 2006, 57(6):655-669.
    • (2006) Journal of the Operational Research Society , vol.57 , Issue.6 , pp. 655-669
    • Finlay, S.M.1
  • 20
    • 24144464528 scopus 로고    scopus 로고
    • Good practice in retail credit scorecard assessment
    • Hand D.J. Good practice in retail credit scorecard assessment. Journal of the Operational Research Society 2005, 56(9):1109-1117.
    • (2005) Journal of the Operational Research Society , vol.56 , Issue.9 , pp. 1109-1117
    • Hand, D.J.1
  • 21
    • 69549133517 scopus 로고    scopus 로고
    • Measuring classifier performance: a coherent alternative to the area under the ROC curve
    • Hand D.J. Measuring classifier performance: a coherent alternative to the area under the ROC curve. Machine Learning 2009, 77:103-123.
    • (2009) Machine Learning , vol.77 , pp. 103-123
    • Hand, D.J.1
  • 22
    • 67649803216 scopus 로고    scopus 로고
    • Mining the past to determine the future: problems and possibilities
    • Hand D.J. Mining the past to determine the future: problems and possibilities. International Journal of Forecasting 2009, 25:441-451.
    • (2009) International Journal of Forecasting , vol.25 , pp. 441-451
    • Hand, D.J.1
  • 25
    • 0030069896 scopus 로고    scopus 로고
    • Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
    • Harrell F.E., Lee K.L., Mark D.B. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statistics in Medicine 1996, 15(4):361-387.
    • (1996) Statistics in Medicine , vol.15 , Issue.4 , pp. 361-387
    • Harrell, F.E.1    Lee, K.L.2    Mark, D.B.3
  • 29
    • 35449000663 scopus 로고    scopus 로고
    • Technology scoring model considering rejected applicants and effect of reject inference
    • Kim Y., Sohn S.Y. Technology scoring model considering rejected applicants and effect of reject inference. Journal of the Operational Research Society 2007, 58(10):1341-1347.
    • (2007) Journal of the Operational Research Society , vol.58 , Issue.10 , pp. 1341-1347
    • Kim, Y.1    Sohn, S.Y.2
  • 30
    • 33845993667 scopus 로고    scopus 로고
    • Instance-based data reduction for improved identification of difficult small classes
    • Laurikkala J. Instance-based data reduction for improved identification of difficult small classes. Intelligent Data Analysis 2002, 6(4):311-322.
    • (2002) Intelligent Data Analysis , vol.6 , Issue.4 , pp. 311-322
    • Laurikkala, J.1
  • 33
    • 84984455297 scopus 로고
    • The flat maximum effect and linear scoring models for prediction
    • Lovie A.D., Lovie P. The flat maximum effect and linear scoring models for prediction. Journal of Forecasting 1986, 5(3):159-168.
    • (1986) Journal of Forecasting , vol.5 , Issue.3 , pp. 159-168
    • Lovie, A.D.1    Lovie, P.2
  • 34
    • 84155194750 scopus 로고    scopus 로고
    • Learning when data sets are imbalanced and when costs are unequal and unknown. In Proceedings of the ICML'03 workshop on learning from imbalanced data sets.
    • Maloof, M. (2003). Learning when data sets are imbalanced and when costs are unequal and unknown. In Proceedings of the ICML'03 workshop on learning from imbalanced data sets.
    • (2003)
    • Maloof, M.1
  • 35
    • 33646263446 scopus 로고    scopus 로고
    • Glenlake Pub. Co. Fitzroy Dearborn Pub., Chicago
    • Mays E. Handbook of credit scoring 2001, Glenlake Pub. Co. Fitzroy Dearborn Pub., Chicago.
    • (2001) Handbook of credit scoring
    • Mays, E.1
  • 39
    • 30944469162 scopus 로고    scopus 로고
    • On preprocessing data for financial credit risk evaluation
    • Piramuthu S. On preprocessing data for financial credit risk evaluation. Expert Systems with Applications 2006, 30:489-497.
    • (2006) Expert Systems with Applications , vol.30 , pp. 489-497
    • Piramuthu, S.1
  • 40
    • 35048878309 scopus 로고    scopus 로고
    • Learning with class skews and small disjuncts
    • Springer, Advances in artificial intelligence-SBIA 2004
    • Prati R.C., Batista G., Monard M.C. Learning with class skews and small disjuncts. Lecture notes in computer science 2004, Vol. 3731:296-306. Springer.
    • (2004) Lecture notes in computer science , vol.3731 , pp. 296-306
    • Prati, R.C.1    Batista, G.2    Monard, M.C.3
  • 44
    • 0034732710 scopus 로고    scopus 로고
    • Prognostic modelling with logistic regression analysis: a comparison of selection methods in small data sets
    • Steyerberg E.W., Eijkemans M.J.C., Harrell F.E., Habbema J., Dik F. Prognostic modelling with logistic regression analysis: a comparison of selection methods in small data sets. Statistics in Medicine 2000, 19(8):1059-1079.
    • (2000) Statistics in Medicine , vol.19 , Issue.8 , pp. 1059-1079
    • Steyerberg, E.W.1    Eijkemans, M.J.C.2    Harrell, F.E.3    Habbema, J.4    Dik, F.5
  • 46
    • 0001466281 scopus 로고    scopus 로고
    • A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers
    • Thomas L.C. A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers. International Journal of Forecasting 2000, 16(2):149-172.
    • (2000) International Journal of Forecasting , vol.16 , Issue.2 , pp. 149-172
    • Thomas, L.C.1
  • 50
    • 22744447363 scopus 로고    scopus 로고
    • The impact of sample bias on consumer credit scoring performance and profitability
    • Verstraeten G., Van den Poel D. The impact of sample bias on consumer credit scoring performance and profitability. Journal of the Operational Research Society 2005, 56(8):981-992.
    • (2005) Journal of the Operational Research Society , vol.56 , Issue.8 , pp. 981-992
    • Verstraeten, G.1    Van den Poel, D.2
  • 51
    • 20844458491 scopus 로고    scopus 로고
    • Mining with rarity: a unifying framework
    • Weiss G.M. Mining with rarity: a unifying framework. ACM SIGKDD Explorations Newsletter 2004, 6(1):7-19.
    • (2004) ACM SIGKDD Explorations Newsletter , vol.6 , Issue.1 , pp. 7-19
    • Weiss, G.M.1
  • 52
    • 1442275185 scopus 로고    scopus 로고
    • Learning when training data are costly: the effect of class distribution on tree induction
    • Weiss G.M., Provost F. Learning when training data are costly: the effect of class distribution on tree induction. Journal of Artificial Intelligence Research 2003, 19:315-354.
    • (2003) Journal of Artificial Intelligence Research , vol.19 , pp. 315-354
    • Weiss, G.M.1    Provost, F.2
  • 53
    • 0034118581 scopus 로고    scopus 로고
    • Neural network credit scoring models
    • West D. Neural network credit scoring models. Computers and Operations Research 2000, 27(11-12):1131-1152.
    • (2000) Computers and Operations Research , vol.27 , Issue.11-12 , pp. 1131-1152
    • West, D.1
  • 54
    • 34447109951 scopus 로고    scopus 로고
    • Handling selection bias when choosing actions in retail credit applications
    • Wu I.-D., Hand D.J. Handling selection bias when choosing actions in retail credit applications. European Journal of Operational Research 2007, 183:1560-1568.
    • (2007) European Journal of Operational Research , vol.183 , pp. 1560-1568
    • Wu, I.-D.1    Hand, D.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.