메뉴 건너뛰기




Volumn 201, Issue 2, 2010, Pages 490-499

Subagging for credit scoring models

Author keywords

Classification; Credit scoring; Decision Support Systems; Risk analysis

Indexed keywords

ADABOOST; BASE CLASSIFIERS; CLASSIFICATION; CLASSIFICATION TECHNIQUE; CREDIT RISKS; CREDIT SCORING; CREDIT SCORING MODEL; CROSS VALIDATION; CUSTOMER CREDITS; ENSEMBLE CLASSIFICATION; IID DATA; LOGISTIC REGRESSIONS; MISSING DATA; MISSING INFORMATION; NEAREST NEIGHBORS; REAL WORLD DATA; REAL-WORLD APPLICATION; RESEARCH TOPICS; ROBUST MODELS; UNBALANCED DATA;

EID: 70349299929     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2009.03.008     Document Type: Article
Times cited : (177)

References (23)
  • 3
    • 33744958288 scopus 로고    scopus 로고
    • Nearest neighbor classification from multiple feature subsets
    • Bay S.D. Nearest neighbor classification from multiple feature subsets. Intelligent Data Analysis 3 3 (1999) 191-209
    • (1999) Intelligent Data Analysis , vol.3 , Issue.3 , pp. 191-209
    • Bay, S.D.1
  • 4
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Machine Learning 24 2 (1996) 123-140.
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 6
    • 33746171809 scopus 로고    scopus 로고
    • Observations on bagging
    • Buja A., and Stuetzle W. Observations on bagging. Statistica Sinica 16 (2006) 323-351
    • (2006) Statistica Sinica , vol.16 , pp. 323-351
    • Buja, A.1    Stuetzle, W.2
  • 9
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • Dietterich T.G. An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Machine Learning 40 2 (2000) 139-158
    • (2000) Machine Learning , vol.40 , Issue.2 , pp. 139-158
    • Dietterich, T.G.1
  • 11
    • 0345438685 scopus 로고    scopus 로고
    • Roc graphs: Notes and practical considerations for data mining researchers
    • Tech. Rep, HP Laboratories, Palo Alto, CA, USA
    • Fawcett, T., 2003. Roc graphs: Notes and practical considerations for data mining researchers. Tech. Rep., HP Laboratories, Palo Alto, CA, USA.
    • (2003)
    • Fawcett, T.1
  • 13
    • 84944837333 scopus 로고
    • Introducing recursive partitioning for financial classification: The case of financial distress
    • Frydman H., Altman E., and Kao D. Introducing recursive partitioning for financial classification: The case of financial distress. Journal of Finance 40 1 (1985) 269-291
    • (1985) Journal of Finance , vol.40 , Issue.1 , pp. 269-291
    • Frydman, H.1    Altman, E.2    Kao, D.3
  • 14
    • 1542603058 scopus 로고    scopus 로고
    • A k-nearest neighbor classifier for assessing consumer risk
    • Henley W., and Hand D. A k-nearest neighbor classifier for assessing consumer risk. Statician 44 1 (1996) 77-95
    • (1996) Statician , vol.44 , Issue.1 , pp. 77-95
    • Henley, W.1    Hand, D.2
  • 15
    • 17844388095 scopus 로고    scopus 로고
    • Hybrid mining approach in the design of credit scoring models
    • Hsieh N. Hybrid mining approach in the design of credit scoring models. Expert Systems with Applications 28 4 (2005) 655-665
    • (2005) Expert Systems with Applications , vol.28 , Issue.4 , pp. 655-665
    • Hsieh, N.1
  • 16
    • 2442665617 scopus 로고    scopus 로고
    • Credit rating analysis with support vector machines and neural networks: A market comparative study
    • Huang Z., Chen H., Hsu C., Chen W., and Wu S. Credit rating analysis with support vector machines and neural networks: A market comparative study. Decision Support Systems 37 (2004) 543-558
    • (2004) Decision Support Systems , vol.37 , pp. 543-558
    • Huang, Z.1    Chen, H.2    Hsu, C.3    Chen, W.4    Wu, S.5
  • 18
    • 17844382437 scopus 로고    scopus 로고
    • A two stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines
    • Lee T., Chiu C., Lu C., and Chen I. A two stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines. Expert Systems with Applications 28 4 (2002) 743-752
    • (2002) Expert Systems with Applications , vol.28 , Issue.4 , pp. 743-752
    • Lee, T.1    Chiu, C.2    Lu, C.3    Chen, I.4
  • 20
    • 16244405300 scopus 로고    scopus 로고
    • Building credit scoring models using genetic programming
    • Ong C., Huang J., and Tzeng G. Building credit scoring models using genetic programming. Expert Systems with Applications 29 1 (2005) 41-47
    • (2005) Expert Systems with Applications , vol.29 , Issue.1 , pp. 41-47
    • Ong, C.1    Huang, J.2    Tzeng, G.3
  • 23
    • 84974012809 scopus 로고
    • A note on the comparison of logit and discriminant models of consumer credit behavior
    • Wiginton J. A note on the comparison of logit and discriminant models of consumer credit behavior. Journal of Financial and Quantitative Analysis 15 (1980) 757-770
    • (1980) Journal of Financial and Quantitative Analysis , vol.15 , pp. 757-770
    • Wiginton, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.