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Volumn 2709, Issue , 2003, Pages 286-295

Ensemble construction via designed output distortion

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERS;

EID: 35248863524     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44938-8_29     Document Type: Article
Times cited : (8)

References (10)
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    • Neural network ensembles, Cross Validation, and Active Learning
    • G. Tesauro, D. S. Touretzky and T. K. Leen, eds. MIT Press, Cambridge, MA
    • Krogh, A. and Vedelsby, J. Neural network ensembles, Cross Validation, and Active Learning. In: G. Tesauro, D. S. Touretzky and T. K. Leen, eds. Advances in Neural Information Processing Systems 7, p. 231-238, MIT Press, Cambridge, MA, 1995.
    • (1995) Advances in Neural Information Processing Systems , vol.7 , pp. 231-238
    • Krogh, A.1    Vedelsby, J.2
  • 2
    • 85127438349 scopus 로고    scopus 로고
    • Learning with ensembles: How over-fitting can be useful
    • D. S. Touretzky, M. C. Mozer and M. E. Hasselmo, eds. MIT Press
    • Sollich, P. and Krogh, A. Learning with ensembles: How over-fitting can be useful. In: D. S. Touretzky, M. C. Mozer and M. E. Hasselmo, eds. Advances in Neural Information Processing Systems 8, p. 190-196, MIT Press, 1996.
    • (1996) Advances in Neural Information Processing Systems , vol.8 , pp. 190-196
    • Sollich, P.1    Krogh, A.2
  • 3
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman, L. Bagging predictors. Machine Learning 24 (2):123-140, 1996.
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 4
    • 0034276320 scopus 로고    scopus 로고
    • Randomizing outputs to increase prediction accuracy
    • September
    • Breiman, L. Randomizing outputs to increase prediction accuracy. Machine Learning, 40 (3): 229-242, September 2000.
    • (2000) Machine Learning , vol.40 , Issue.3 , pp. 229-242
    • Breiman, L.1
  • 5
    • 0013287013 scopus 로고    scopus 로고
    • Bootstrapping with noise: An effective regularization technique
    • Connection Science
    • Raviv, Y. and Intrator. N. Bootstrapping with noise: An effective regularization technique. Connection Science, Special issue on Combining Estimators, 8:356-372, 1996.
    • (1996) Combining Estimators , vol.8 , Issue.SPEC. ISSUE , pp. 356-372
    • Raviv, Y.1    Intrator, N.2
  • 6
    • 35248848262 scopus 로고    scopus 로고
    • Variance reduction via noise and bias constraints
    • Sharkey, A. J. C. (Ed.) Springer Verlag.
    • Raviv, Y. and Intrator, N. Variance reduction via noise and bias constraints. In: Sharkey, A. J. C. (Ed.) Combining Artificial Neural Nets. Springer Verlag. 1999.
    • (1999) Combining Artificial Neural Nets
    • Raviv, Y.1    Intrator, N.2
  • 7
    • 0003408496 scopus 로고
    • University of California, Department of Information and Computer Science. Irvine, CA
    • Murphy, P. M. & Aha, D. W. UCI Repository of machine learning databases. University of California, Department of Information and Computer Science. Irvine, CA 1994.
    • (1994) UCI Repository of Machine Learning Databases
    • Murphy, P.M.1    Aha, D.W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.