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Volumn 2366 LNAI, Issue , 2002, Pages 592-599

Feature selection for ensembles of simple Bayesian classifiers

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL STORAGE; INTEGRATION; INTELLIGENT SYSTEMS;

EID: 78650176398     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48050-1_63     Document Type: Conference Paper
Times cited : (10)

References (17)
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    • Bauer, E., Kohavi, R.: An empirical comparison of voting classification algorithms: bagging, boosting, and variants. Machine Learning, Vol. 36, Nos. 1,2 (1999) 105-139.
    • (1999) Machine Learning , vol.36 , Issue.1-2 , pp. 105-139
    • Bauer, E.1    Kohavi, R.2
  • 2
    • 0003408496 scopus 로고    scopus 로고
    • Dep-t of Information and CS, Un-ty of California, Irvine CA
    • Blake, C.L., Merz, C.J.: UCI repository of machine learning databases [http:// www.ics.uci.edu/ ~mlearn/ MLRepository.html]. Dep-t of Information and CS, Un-ty of California, Irvine CA (1998).
    • (1998) UCI Repository of Machine Learning Databases
    • Blake, C.L.1    Merz, C.J.2
  • 4
    • 0003954942 scopus 로고    scopus 로고
    • Diversity versus quality in classification ensembles based on feature selection
    • Trinity College Dublin, Ireland
    • Cunningham, P.: Diversity versus quality in classification ensembles based on feature selection. Tech. Report TCD-CS-2000-02, Dept. of Computer Science, Trinity College Dublin, Ireland (2000).
    • (2000) Tech. Report TCD-CS-2000-02, Dept. of Computer Science
    • Cunningham, P.1
  • 6
    • 0031269184 scopus 로고    scopus 로고
    • On the optimality of the simple Bayesian classifier under zero-one loss
    • Domingos, P., Pazzani, M.: On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning, Vol. 29, Nos. 2,3 (1997) 103-130.
    • (1997) Machine Learning , vol.29 , Issue.2-3 , pp. 103-130
    • Domingos, P.1    Pazzani, M.2
  • 7
    • 0003642109 scopus 로고    scopus 로고
    • Tech. Report CS97-557, Dept. of CS and Engineering, Un-ty of California, San Diego, USA
    • Elkan C.: Boosting and naïve Bayesian learning. Tech. Report CS97-557, Dept. of CS and Engineering, Un-ty of California, San Diego, USA (1997).
    • (1997) Boosting and Naïve Bayesian Learning
    • Elkan, C.1
  • 11
    • 85054435084 scopus 로고
    • Neural network ensembles, cross validation, and active learning
    • D. Touretzky, T. Leen (eds.), Cambridge, MA, MIT Press
    • Krogh, A., Vedelsby, J.: Neural network ensembles, cross validation, and active learning.In D. Touretzky, T. Leen (eds.), Advances in Neural Information Processing Systems, Vol. 7, Cambridge, MA, MIT Press (1995) 231-238.
    • (1995) Advances in Neural Information Processing Systems , vol.7 , pp. 231-238
    • Krogh, A.1    Vedelsby, J.2
  • 14
    • 84957702069 scopus 로고    scopus 로고
    • A dynamic integration algorithm for an ensemble of classifiers
    • Z.W. Ras, A. Skowron (eds.), Springer-Verlag, Warsaw
    • Puuronen, S., Terziyan, V., Tsymbal, A.: A dynamic integration algorithm for an ensemble of classifiers. In: Z.W. Ras, A. Skowron (eds.), Foundations of Intelligent Systems: ISMIS'99, Lecture Notes in AI, Vol. 1609, Springer-Verlag, Warsaw (1999) 592-600.
    • (1999) Foundations of Intelligent Systems: ISMIS'99, Lecture Notes in AI , vol.1609 , pp. 592-600
    • Puuronen, S.1    Terziyan, V.2    Tsymbal, A.3
  • 16
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    • Bagging and the random subspace method for redundant feature spaces
    • J. Kittler, F. Roli (eds.), Cambridge, UK
    • Skurichina, M., Duin, R.P.W.: Bagging and the random subspace method for redundant feature spaces. In: J. Kittler, F. Roli (eds.), Proc. 2nd Int. Workshop on Multiple Classifier Systems MCS 2001, Cambridge, UK (2001) 1-10.
    • (2001) Proc. 2nd Int. Workshop on Multiple Classifier Systems MCS 2001 , pp. 1-10
    • Skurichina, M.1    Duin, R.P.W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.