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Volumn , Issue , 2004, Pages 755-760

A DEA approach for model combination

Author keywords

Data Envelopment Analysis; Model Combination; ROC

Indexed keywords

ARTIFICIAL INTELLIGENCE; BENCHMARKING; BINARY SEQUENCES; CLASSIFICATION (OF INFORMATION); DATA MINING; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; PROBLEM SOLVING;

EID: 12244251828     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1014052.1014152     Document Type: Conference Paper
Times cited : (6)

References (15)
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    • (1996) Machine Learning , vol.24 , Issue.3 , pp. 173-202
    • Ali, K.M.1    Pazzani, M.J.2
  • 2
    • 0021497874 scopus 로고
    • Some models for estimating technical and scale inefficiencies in data envelopment analysis
    • Banker, R. D., A. Chanes, W.W. Cooper. 1984. Some Models for estimating Technical and Scale Inefficiencies In Data Envelopment Analysis. Management Science, 30(9): 1078-1092.
    • (1984) Management Science , vol.30 , Issue.9 , pp. 1078-1092
    • Banker, R.D.1    Chanes, A.2    Cooper, W.W.3
  • 4
    • 0032645080 scopus 로고    scopus 로고
    • An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
    • Bauer, E., Kohavi, R. 1999. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants. Machine Learning, 36(1): 105-142.
    • (1999) Machine Learning , vol.36 , Issue.1 , pp. 105-142
    • Bauer, E.1    Kohavi, R.2
  • 6
    • 45249128876 scopus 로고
    • Combining forecasts: A review and annoted bibliography
    • Clemen, R. T. 1989. Combining Forecasts: A review and annoted bibliography. International Journal of Forecasting, 5: 559-583.
    • (1989) International Journal of Forecasting , vol.5 , pp. 559-583
    • Clemen, R.T.1
  • 9
    • 80053403826 scopus 로고    scopus 로고
    • Ensemble methods in machine learning
    • Dietterich, T. 2000. Ensemble Methods in Machine Learning. Multiple Classifier Systems. 18, 1-15.
    • (2000) Multiple Classifier Systems , vol.18 , pp. 1-15
    • Dietterich, T.1
  • 10
    • 12244262552 scopus 로고    scopus 로고
    • Convex hull machine for regression and classification
    • Kim, Y., J. Kim, J. Jongwoo. 2002 Convex hull machine for regression and classification. IEEE Conference on Data Mining 2002. 243-253.
    • (2002) IEEE Conference on Data Mining , vol.2002 , pp. 243-253
    • Kim, Y.1    Kim, J.2    Jongwoo, J.3
  • 11
    • 79957446532 scopus 로고    scopus 로고
    • Position paper: Extensions of ROC analysis to multi-class domains
    • Paper presented at the, Stanford
    • Lane, T. 2000. Position Paper: Extensions of ROC Analysis to Multi-Class Domains. Paper presented at the Proceedings of ICML-2000 Workshop on Cost-Sensitive Learning, Stanford.
    • (2000) Proceedings of ICML-2000 Workshop on Cost-Sensitive Learning
    • Lane, T.1
  • 13
    • 0035283313 scopus 로고    scopus 로고
    • Robust classification for imprecise environment
    • Provost, F. and T. Fawcett. 2001. Robust Classification for Imprecise Environment. Machine Learning 42, 203-231.
    • (2001) Machine Learning , vol.42 , pp. 203-231
    • Provost, F.1    Fawcett, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.