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Volumn , Issue , 2004, Pages 448-456

A hybrid decision support tool using ensemble of classifiers

Author keywords

Artificial intelligence; Decision support systems

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BENCHMARKING; CLASSIFICATION (OF INFORMATION); DATA REDUCTION; FORECASTING; NEURAL NETWORKS; PROBLEM SOLVING;

EID: 8444242169     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (23)
  • 1
    • 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, 105-139.
    • (1999) Machine Learning , vol.36 , pp. 105-139
    • Bauer, E.1    Kohavi, R.2
  • 2
    • 0003408496 scopus 로고    scopus 로고
    • Irvine, CA: University of California, Department of Information and Computer Science
    • Blake, C.L., Merz, C.J, 1998. UCI Repository of machine learning databases. Irvine, CA: University of California, Department of Information and Computer Science. (www.ics.uci.edu/~mlearn/MLRepository.html)
    • (1998) UCI Repository of Machine Learning Databases
    • Blake, C.L.1    Merz, C.J.2
  • 3
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman, L, 1996. Bagging Predictors. Machine Learning 24, 123-140.
    • (1996) Machine Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 4
    • 80053403826 scopus 로고    scopus 로고
    • Ensemble methods in machine learning
    • Kittler, J., Roli, F., eds. Multiple Classifier Systems, Springer
    • Dietterich, T.G, 2001. Ensemble methods in machine learning. In Kittler, J., Roli, F., eds. Multiple Classifier Systems. LNCS Vol. 1857, Springer, 1-15.
    • (2001) LNCS , vol.1857 , pp. 1-15
    • Dietterich, T.G.1
  • 5
    • 65449131755 scopus 로고    scopus 로고
    • Is combining classifiers better than selecting the best one
    • Dzeroski, S., Zenko, B., 2002. Is Combining Classifiers Better than Selecting the Best One. ICML 2002: 123130.
    • (2002) ICML 2002 , pp. 123-130
    • Dzeroski, S.1    Zenko, B.2
  • 7
    • 0002978642 scopus 로고    scopus 로고
    • Experiments with a new boosting algorithm
    • Freund, Y., Schapire, R., 1996. Experiments with a New Boosting Algorithm, Proceedings: ICML'96, p. 148-156.
    • (1996) Proceedings: ICML'96 , pp. 148-156
    • Freund, Y.1    Schapire, R.2
  • 12
    • 0000551189 scopus 로고    scopus 로고
    • Popular ensemble methods: An empirical study
    • Morgan Kaufmann
    • Opitz, D., Maclin, R., 1999. Popular Ensemble Methods: An Empirical Study, Artificial Intelligence Research 11,169-198, Morgan Kaufmann.
    • (1999) Artificial Intelligence Research , vol.11 , pp. 169-198
    • Opitz, D.1    Maclin, R.2
  • 14
    • 27144463192 scopus 로고    scopus 로고
    • On comparing classifiers: Pitfalls to avoid and a recommended approach
    • Salzberg, S., 1997. On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach, Data Mining and Knowledge Discovery 1, 317-328.
    • (1997) Data Mining and Knowledge Discovery , vol.1 , pp. 317-328
    • Salzberg, S.1
  • 15
    • 0000245470 scopus 로고
    • Selecting a classification method by cross-validation
    • Schaffer, C., 1993. Selecting a classification method by cross-validation. Machine Learning 13,135-143.
    • (1993) Machine Learning , vol.13 , pp. 135-143
    • Schaffer, C.1
  • 16
    • 0032280519 scopus 로고    scopus 로고
    • Boosting the margin: A new explana-tion for the effectiveness of voting methods
    • Schapire, R. E., Freund, Y., Bartlett, P., & Lee, W. S., 1998, Boosting the margin: A new explana-tion for the effectiveness of voting methods. The Annals of Statistics 26,1651-1686.
    • (1998) The Annals of Statistics , vol.26 , pp. 1651-1686
    • Schapire, R.E.1    Freund, Y.2    Bartlett, P.3    Lee, W.S.4
  • 18
    • 8444229122 scopus 로고    scopus 로고
    • How to make stacking better and faster while also taking care of an unknown weakness
    • Sammut C., Hoffmann A. (eds.), Morgan Kaufmann Publishers
    • Seewald, A.K, 2002. How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness, in Sammut C., Hoffmann A. (eds.), Proceedings of the Nineteenth International Conference on Machine Learning (ICML 2002), Morgan Kaufmann Publishers, pp.554-561.
    • (2002) Proceedings of the Nineteenth International Conference on Machine Learning (ICML 2002) , pp. 554-561
    • Seewald, A.K.1
  • 19
    • 0033343146 scopus 로고    scopus 로고
    • Issues in stacked generalization
    • Morgan Kaufmann
    • Ting, K., & Witten, I., 1999. Issues in Stacked Generalization, Artificial Intelligence Research 10, 271-289, Morgan Kaufmann.
    • (1999) Artificial Intelligence Research , vol.10 , pp. 271-289
    • Ting, K.1    Witten, I.2
  • 23
    • 0026692226 scopus 로고
    • Stacked Generalization
    • Wolpert, D., 1992, Stacked Generalization. Neural Networks 5, 241-260.
    • (1992) Neural Networks , vol.5 , pp. 241-260
    • Wolpert, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.