Communications for Statistical Applications and Methods

  • 제4권3호
  • /
  • Pages.827-832
  • /
  • 1997
  • /
  • 2287-7843(pISSN)
  • /
  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지

Bootstrap Model Selection Criterion for Determining the Number of Hidden Units in Neural Network Model

  • Hwang, Changha (Dept. of Statistical Information, Catholic University of Taegu-Hyosung) ;
  • Kim, Daehak (Dept. of Statistical Information, Catholic University of Taegu-Hyosung)
  • 발행 : 1997.12.01
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초록

Statistical relations between a system and empirical distribution are studied in terms of the concept of Akaike's Information Criterion. From this consideration we derive a bootstrap criterion for determining the optimal number of hidden units in nerual networks.

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참고문헌

  1. IEEE Transactions on Electronic Computers v.EC-16 Theory of adaptive pattern classifiers Amari, S.
  2. Neurocomputing v.5 Backpropagation and stochastic gradient descent method Amari, S.
  3. Statistics and Probability Letters v.26 A note on bootstrap model selection criterion Chung, H.;Lee, K.;Koo, J.
  4. Model Selection Linhart, H.;Zucchini, W.
  5. Neural Networks v.8 Unbiased estimate of generalization error and model selection in neural network Liu, Y.
  6. Artificial Neural Networks A criterion for determining the number of parameters in an artificial neural network model Murata, N.;Yoshizawa, S.;Amari, S.;T. Kohonen(et al.)(ed.)
  7. IEEE Transactions on Neural Networks v.5 Network information criterion - Determining the number of hidden units for an artificial neural network model Murata, N.;Yoshizawa, S.;Amari, S.