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Volumn 15, Issue 7, 2003, Pages 1691-1714

Comparison of model selection for regression

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; COMPARATIVE STUDY; REGRESSION ANALYSIS; THEORETICAL MODEL;

EID: 0037484691     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976603321891864     Document Type: Article
Times cited : (128)

References (15)
  • 1
    • 51249190305 scopus 로고
    • Statistical prediction information
    • Akaike, H. (1970). Statistical prediction information. Ann. Inst. Statist. Math, 22, 203-217.
    • (1970) Ann. Inst. Statist. Math , vol.22 , pp. 203-217
    • Akaike, H.1
  • 3
    • 0036643075 scopus 로고    scopus 로고
    • Model selection for small sample regression
    • Chapelle, O., Vapnik, V., & Bengio, Y (2002). Model selection for small sample regression. Machine Learning, 48(1), 9-23.
    • (2002) Machine Learning , vol.48 , Issue.1 , pp. 9-23
    • Chapelle, O.1    Vapnik, V.2    Bengio, Y.3
  • 5
    • 0032595046 scopus 로고    scopus 로고
    • Model complexity control for regression using VC generalization bounds
    • Cherkassky, V., Shao, X., Mulier, F., & Vapnik, V. (1999). Model complexity control for regression using VC generalization bounds. IEEE Transactions on Neural Networks, 10(5), 1075-1089.
    • (1999) IEEE Transactions on Neural Networks , vol.10 , Issue.5 , pp. 1075-1089
    • Cherkassky, V.1    Shao, X.2    Mulier, F.3    Vapnik, V.4
  • 6
    • 0035190688 scopus 로고    scopus 로고
    • Signal estimation and denoising using VC-theory
    • Cherkassky, V., & Shao, X. (2001). Signal estimation and denoising using VC-theory. Neural Networks, 14, 37-52.
    • (2001) Neural Networks , vol.14 , pp. 37-52
    • Cherkassky, V.1    Shao, X.2
  • 7
    • 0034842313 scopus 로고    scopus 로고
    • Myopotential denoising of ECG signals using wavelet thresholding methods
    • Cherkassky, V., & Kilts, S. (2001). Myopotential denoising of ECG signals using wavelet thresholding methods. Neural Networks, 14, 1129-1137.
    • (2001) Neural Networks , vol.14 , pp. 1129-1137
    • Cherkassky, V.1    Kilts, S.2
  • 12
    • 0034241362 scopus 로고    scopus 로고
    • Measuring the VC-dimension using optimized experimental design
    • Shao, X., Cherkassky, V., & Li, W. (2000). Measuring the VC-dimension using optimized experimental design. Neural Computation, 12, 1969-1986.
    • (2000) Neural Computation , vol.12 , pp. 1969-1986
    • Shao, X.1    Cherkassky, V.2    Li, W.3
  • 15
    • 0001205879 scopus 로고
    • Measuring the VC-dimension of a learning machine
    • Vapnik, V. Levin, E., & Cun, Y. (1994). Measuring the VC-dimension of a learning machine. Neural Computation, 6, 851-876.
    • (1994) Neural Computation , vol.6 , pp. 851-876
    • Vapnik, V.1    Levin, E.2    Cun, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.