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Volumn 16, Issue 2, 2007, Pages 109-124

Evaluation of neural network performance and generalisation using thresholding functions

Author keywords

Neural network training and generalisation; Thresholding

Indexed keywords


EID: 33847271203     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-006-0044-z     Document Type: Article
Times cited : (3)

References (16)
  • 1
    • 0024771475 scopus 로고
    • Pattern classification using neural networks
    • Lippmann RP (1989) Pattern classification using neural networks. IEEE Commun Mag 47(11):47-64
    • (1989) IEEE Commun Mag , vol.47 , Issue.11 , pp. 47-64
    • Lippmann, R.P.1
  • 3
    • 0036127092 scopus 로고    scopus 로고
    • A review of evidence of health benefit from artificial neural networks in medical intervention
    • Lisboa PJG (2002) A review of evidence of health benefit from artificial neural networks in medical intervention. Neural Netw 15:11-39
    • (2002) Neural Netw , vol.15 , pp. 11-39
    • Lisboa, P.J.G.1
  • 4
    • 4344641278 scopus 로고    scopus 로고
    • A principled approach for building and evaluating neural network classification models
    • Berardi VL, Patuwo BE, Hu MY (2004) A principled approach for building and evaluating neural network classification models. Decis Support Syst 38:233-246
    • (2004) Decis Support Syst , vol.38 , pp. 233-246
    • Berardi, V.L.1    Patuwo, B.E.2    Hu, M.Y.3
  • 5
    • 0037143140 scopus 로고    scopus 로고
    • Neural network classification and novelty detection
    • Augusteijn MF, Folkert BA (2002) Neural network classification and novelty detection. Int J Remote Sens 23(14):2891-2902
    • (2002) Int J Remote Sens , vol.23 , Issue.14 , pp. 2891-2902
    • Augusteijn, M.F.1    Folkert, B.A.2
  • 6
    • 0030124529 scopus 로고    scopus 로고
    • Neural network classification of flaws detected by ultrasonic means
    • Masnata A, Sunseri M (1996) Neural network classification of flaws detected by ultrasonic means. NDT&E Int 29(2):97-93
    • (1996) NDT&E Int , vol.29 , Issue.2 , pp. 97-93
    • Masnata, A.1    Sunseri, M.2
  • 7
    • 0037250871 scopus 로고    scopus 로고
    • Manson G, Worden K, Allman D (2003a) Experimental validation of a structural health monitoring methodology. Part II. Novelty detection on a Gnat aircraft. J Sound Vib 259(2):345-363
    • Manson G, Worden K, Allman D (2003a) Experimental validation of a structural health monitoring methodology. Part II. Novelty detection on a Gnat aircraft. J Sound Vib 259(2):345-363
  • 8
    • 0037247230 scopus 로고    scopus 로고
    • Manson G, Worden K, Allman D (2003b) Experimental validation of a structural health monitoring methodology. Part III. Damage location on an aircraft wing. J Sound Vib 259(2):365-385
    • Manson G, Worden K, Allman D (2003b) Experimental validation of a structural health monitoring methodology. Part III. Damage location on an aircraft wing. J Sound Vib 259(2):365-385
  • 9
    • 0043126911 scopus 로고    scopus 로고
    • Logistic regression and artificial neural network classification models; a methodology review
    • Dreiseitl S, Ohno-Machado L (2002) Logistic regression and artificial neural network classification models; a methodology review. J Biomed Inform 35:352-359
    • (2002) J Biomed Inform , vol.35 , pp. 352-359
    • Dreiseitl, S.1    Ohno-Machado, L.2
  • 11
    • 0034728368 scopus 로고    scopus 로고
    • On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology
    • Schwarzer G, Vach W, Schumacher M (2000) On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology. Stat Med 19:541-561
    • (2000) Stat Med , vol.19 , pp. 541-561
    • Schwarzer, G.1    Vach, W.2    Schumacher, M.3
  • 15
    • 0002704818 scopus 로고
    • A practical Bayesian framework for backpropagation networks
    • MacKay DJC (1992) A practical Bayesian framework for backpropagation networks. Neural Comput 4:448-472
    • (1992) Neural Comput , vol.4 , pp. 448-472
    • MacKay, D.J.C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.