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Volumn 5, Issue 3, 1997, Pages 134-151

Estimating MLP generalisation ability without a test set using fast, approximate leave-one-out cross-validation

Author keywords

Cross validation; Generalisation; Leverage; Model selection; Multilayer perceptron regression model; Prediction error

Indexed keywords


EID: 21744444261     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF01413859     Document Type: Article
Times cited : (9)

References (8)
  • 1
    • 0000581356 scopus 로고
    • Introduction to kernel and nearest-neighbour nonparametric regression
    • Altman NS. Introduction to kernel and nearest-neighbour nonparametric regression. The American Statistician 1992; 46: 175-185
    • (1992) The American Statistician , vol.46 , pp. 175-185
    • Altman, N.S.1
  • 3
    • 0026245032 scopus 로고
    • System identification of a biochemical process using feed-forward neural networks
    • Bulsari A, Saxen H. System identification of a biochemical process using feed-forward neural networks. Neurocomputing 1991; 3: 125-133
    • (1991) Neurocomputing , vol.3 , pp. 125-133
    • Bulsari, A.1    Saxen, H.2
  • 4
    • 0025414780 scopus 로고
    • Modelling chemical process systems via neural computation
    • April
    • Bhat NV, Minderman PA, McAvoy T. Modelling chemical process systems via neural computation. IEEE Control Systems 1990; 24-30, April
    • (1990) IEEE Control Systems , pp. 24-30
    • Bhat, N.V.1    Minderman, P.A.2    McAvoy, T.3
  • 6
    • 31844454536 scopus 로고
    • Application of neural network methodology to the modelling of the yield strength in a steel rolling plate mill
    • RP Lippman, JE Moody, SJ Hanson (eds), 698-705, Morgan Kaufmann
    • Tsoi AC. Application of neural network methodology to the modelling of the yield strength in a steel rolling plate mill. In: Advances in Neural Information Processing Systems 4, RP Lippman, JE Moody, SJ Hanson (eds), 698-705, Morgan Kaufmann, 1992
    • (1992) Advances in Neural Information Processing Systems , vol.4
    • Tsoi, A.C.1
  • 7
    • 0024880831 scopus 로고
    • Multilayer feedforward neural networks are universal approximators
    • Hornik K, Stinchcombe M, White H. Multilayer feedforward neural networks are universal approximators. Neural Networks 1989; 2: 359-366
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.