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Volumn , Issue , 2006, Pages 828-833

Getting the most out of ensemble selection

Author keywords

[No Author keywords available]

Indexed keywords

ARBITRARY METRICS; ENSEMBLE SELECTION;

EID: 48749096852     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2006.76     Document Type: Conference Paper
Times cited : (134)

References (14)
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    • Getting the most out of ensemble selection
    • Technical Report 2006-2045, Cornell University, September, Full version of paper published at ICDM
    • R. Caruana, A. Munson, and A. Niculescu-Mizil. Getting the most out of ensemble selection. Technical Report 2006-2045, Cornell University, September 2006. Full version of paper published at ICDM 2006.
    • (2006)
    • Caruana, R.1    Munson, A.2    Niculescu-Mizil, A.3
  • 3
    • 14344255621 scopus 로고    scopus 로고
    • R. Caruana, A. Niculescu-Mizil, G. Crew, and A. Ksikes. Ensemble selection from libraries of models. In ICML, 2004.
    • R. Caruana, A. Niculescu-Mizil, G. Crew, and A. Ksikes. Ensemble selection from libraries of models. In ICML, 2004.
  • 4
    • 0013396180 scopus 로고    scopus 로고
    • Bayesian averaging of classifiers and the overfitting problem
    • Morgan Kaufmann, San Francisco, CA
    • P. Domingos. Bayesian averaging of classifiers and the overfitting problem. In ICML Morgan Kaufmann, San Francisco, CA, 2000.
    • (2000) ICML
    • Domingos, P.1
  • 5
    • 33751584745 scopus 로고    scopus 로고
    • The combining classifier: To train or not to train?
    • R. P. W. Duin. The combining classifier: To train or not to train? In ICPR (2), 2002.
    • (2002) ICPR , vol.2
    • Duin, R.P.W.1
  • 6
    • 0002289220 scopus 로고    scopus 로고
    • Pruning adaptive boosting
    • Morgan Kaufmann
    • D. D. Margineantu and T. G. Dietterich. Pruning adaptive boosting. In ICML. Morgan Kaufmann, 1997.
    • (1997) ICML
    • Margineantu, D.D.1    Dietterich, T.G.2
  • 7
    • 33749247099 scopus 로고    scopus 로고
    • Pruning in ordered bagging ensembles
    • New York, NY, USA, ACM Press
    • G. Martínez-Munoz and A. Suárez. Pruning in ordered bagging ensembles. In ICML, New York, NY, USA, 2006. ACM Press.
    • (2006) ICML
    • Martínez-Munoz, G.1    Suárez, A.2
  • 8
    • 38049137059 scopus 로고    scopus 로고
    • Optimizing to arbitrary NLP metrics using ensemble selection
    • A. Munson, C. Cardie, and R. Caruana. Optimizing to arbitrary NLP metrics using ensemble selection. In HLT-EMNLP, 2005.
    • (2005) HLT-EMNLP
    • Munson, A.1    Cardie, C.2    Caruana, R.3
  • 9
    • 31844433358 scopus 로고    scopus 로고
    • Predicting good probabilities with supervised learning
    • A. Niculescu-Mizil and R. Caruana. Predicting good probabilities with supervised learning. In ICML'05, 2005.
    • (2005) ICML'05
    • Niculescu-Mizil, A.1    Caruana, R.2
  • 10
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparison to regularized likelihood methods
    • J. Piatt. Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. In Adv. in Large Margin Classifiers, 1999.
    • (1999) Adv. in Large Margin Classifiers
    • Piatt, J.1
  • 12
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    • W. N. Street and Y.-H. Kim. A streaming ensemble algorithm (SEA) for large-scale classification. In KDD, 2001.
    • W. N. Street and Y.-H. Kim. A streaming ensemble algorithm (SEA) for large-scale classification. In KDD, 2001.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.