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Volumn 2, Issue , 1997, Pages 1088-1092

Stopped training via algebraic online estimation of the expected test-set error

Author keywords

[No Author keywords available]

Indexed keywords

GENERALIZATION PERFORMANCE; ITERATIVE OPTIMIZATION; LOCAL MINIMUMS; NEURAL NETWORK MODEL; OBJECTIVE FUNCTIONS; ON-LINE ESTIMATION; OVERFITTING; STOPPING TIME;

EID: 0030718027     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.616180     Document Type: Conference Paper
Times cited : (2)

References (11)
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    • S. Farlow, editor Marcel Dekker, New York
    • A. Barron. Predicted squared error: a criterion for automatic model selection. In S. Farlow, editor, Self-Organizing Methods in Modeling. Marcel Dekker, New York, 1984.
    • (1984) Self-Organizing Methods in Modeling
    • Barron, A.1
  • 2
    • 2642652366 scopus 로고
    • Generalization dynamics in LMS trained linear networks
    • R. P. Lippman, J. E. Moody, and D. S. Touretzky, editors Morgan Kaufmann Publishers, San Mateo, CA
    • Y. Chauvin. Generalization dynamics in LMS trained linear networks. In R. P. Lippman, J. E. Moody, and D. S. Touretzky, editors, Advances in Neural Information Processing Systems 3, pages 890-896. Morgan Kaufmann Publishers, San Mateo, CA, 1991.
    • (1991) Advances in Neural Information Processing Systems , vol.3 , pp. 890-896
    • Chauvin, Y.1
  • 3
    • 0027294340 scopus 로고
    • Improving model selection by nonconvergent methods
    • W. Finnoff, F. Hergert, and H. G. Zimmermann. Improving model selection by nonconvergent methods. Neural Net-works, 6:771-783,1993.
    • (1993) Neural Net-works , vol.6 , pp. 771-783
    • Finnoff, W.1    Hergert, F.2    Zimmermann, H.G.3
  • 4
    • 0001942829 scopus 로고
    • Neural networks and the bias/variance dilemma
    • S. Geman, E. Bienenstock, and R. Doursat. Neural networks and the bias/variance dilemma. Neural Computation, 4( 1): 1-58,1992.
    • (1992) Neural Computation , vol.4 , Issue.1 , pp. 1-58
    • Geman, S.1    Bienenstock, E.2    Doursat, R.3
  • 6
    • 84892142484 scopus 로고
    • Weight-space probability densities and convergence times for stochastic learning
    • Baltimore MD
    • T. K. Leen and G. B. Orr. Weight-space probability densities and convergence times for stochastic learning. In Int. Joint Conference on Neural Networks, volume 4, pages 158-164, Baltimore, MD, 1992.
    • (1992) Int. Joint Conference on Neural Networks , vol.4 , pp. 158-164
    • Leen, T.K.1    Orr, G.B.2
  • 7
    • 0002787457 scopus 로고
    • Architecture selection strategies for neural networks: Application to corporate bond rating prediction
    • A. N. Refenes, editor John Wiley & Sons
    • J. Moody and J. Utans. Architecture selection strategies for neural networks: Application to corporate bond rating prediction. In A. N. Refenes, editor, Neural Networks in the Captial Markets. John Wiley & Sons, 1994.
    • (1994) Neural Networks in the Captial Markets
    • Moody, J.1    Utans, J.2
  • 8
    • 0026289079 scopus 로고
    • Note on generalization, regularization and architecture selection in nonlinear learning systems
    • B. H. Juang, S. Y. Kung, and C. A. Kamm, editors IEEE Signal Processing Society
    • J. E. Moody. Note on generalization, regularization and architecture selection in nonlinear learning systems. In B. H. Juang, S. Y. Kung, and C. A. Kamm, editors, Neural Networks for Signal Processing, pages 1-10. IEEE Signal Processing Society, 1991.
    • (1991) Neural Networks for Signal Processing , pp. 1-10
    • Moody, J.E.1
  • 10
    • 0000319198 scopus 로고
    • Cross-validation:A review
    • Ser. Statistics
    • M. Stone. Cross-validation: A review. Math. Operations-forsch. Statist., Ser. Statistics, 9(1), 1978.
    • (1978) Math. Operations-forsch. Statist , vol.9 , pp. 1
    • Stone, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.