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Volumn , Issue , 2003, Pages 499-504

Monte Carlo theory as an explanation of bagging and boosting

Author keywords

[No Author keywords available]

Indexed keywords

ENSEMBLE LEARNING; MONTE CARLO ALGORITHMS; MONTE CARLO THEORY;

EID: 14344254249     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (18)
  • 1
    • 0032645080 scopus 로고    scopus 로고
    • An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
    • E. Bauer and R. Kohavi. An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 56:105-139.
    • Machine Learning , vol.56 , pp. 105-139
    • Bauer, E.1    Kohavi, R.2
  • 3
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman. Bagging predictors. Machine Learning, 24(2):123-140, 1996. (Pubitemid 126724382)
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 4
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • L. Breiman. Arcing classifiers. The Annals of Statistics, 26(3):801-849, 1998. (Pubitemid 128450035)
    • (1998) Annals of Statistics , vol.26 , Issue.3 , pp. 801-849
    • Breiman, L.1
  • 7
    • 85156217048 scopus 로고    scopus 로고
    • Boosting decision trees
    • David S. Touretzky, Michael C. Mozer, and Michael E. Hasselmo (Eds.), The MIT Press
    • Drucker and Cortes, Boosting decision trees. In David S. Touretzky, Michael C. Mozer, and Michael E. Hasselmo (Eds.), Advances in Neural Information Processing Systems, Vol. 8, (pp. 479-485), The MIT Press, 1996.
    • (1996) Advances in Neural Information Processing Systems , vol.8 , pp. 479-485
    • Drucker1    Cortes2
  • 10
    • 58149321460 scopus 로고
    • Boosting a weak learning algorithm by majority
    • Y. Freund. Boosting a weak learning algorithm by majority. Information and Computation, 2(121):256-2%5, 1995.
    • (1995) Information and Computation , vol.2 , Issue.121 , pp. 256-265
    • Freund, Y.1
  • 11
    • 0031211090 scopus 로고    scopus 로고
    • A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
    • Y. Freund and R. Schapire, A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1):119-139, 1997.*(Pubitemid 127433398)
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 12
    • 0001408126 scopus 로고    scopus 로고
    • Discussion of the paper "arcing classifiers" by Leo Breiman
    • Y. Freund and R. Schapire. Discussion of the paper "arcing classifiers" by Leo Breiman. The Annals of Statistics, 26(3):824-832, 1998.
    • (1998) The Annals of Statistics , vol.26 , Issue.3 , pp. 824-832
    • Freund, Y.1    Schapire, R.2
  • 16
    • 0035370188 scopus 로고    scopus 로고
    • Drifting games
    • DOI 10.1023/A:1010800213066
    • R. Schapire. Drifting games. Machine Learning 43(3): 265-291,2001. (Pubitemid 32471835)
    • (2001) Machine Learning , vol.43 , Issue.3 , pp. 265-291
    • Schapire, R.E.1
  • 17
    • 0032280519 scopus 로고    scopus 로고
    • Boosting the margin: A new explanation for the effectiveness of voting methods
    • R. Schapire, Y. Freund, P. Bartlett, and W. Lee. Boosting the margin: A new explanation for the effectiveness of voting methods. Annals of Statistic, 26(5): 1651-1686, 1998. (Pubitemid 128376902)
    • (1998) Annals of Statistics , vol.26 , Issue.5 , pp. 1651-1686
    • Schapire, R.E.1    Freund, Y.2    Bartlett, P.3    Lee, W.S.4
  • 18
    • 0026692226 scopus 로고
    • Stacked Generalization
    • D. Wolpert. Stacked Generalization, Neural Networks, 5, 241-259, 1992.
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.