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Volumn 3, Issue 1, 2003, Pages 73-98

Data-dependent margin-based generalization bounds for classification

Author keywords

Classification; Error estimation; Fat shattering dimension; Margin based bounds

Indexed keywords

ERROR ANALYSIS; NEURAL NETWORKS; PROBABILITY;

EID: 0042967689     PISSN: 15324435     EISSN: None     Source Type: Journal    
DOI: 10.1162/153244303768966111     Document Type: Article
Times cited : (38)

References (20)
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    • P.L. Bartlett and S. Mendelson. Rademacher and gaussian complexities: risk bounds and structural results. Journal of Machine Learning Research, to appear, 2002.
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  • 11
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    • Kearns, M.1    Schapire, R.E.2
  • 13
    • 0036104545 scopus 로고    scopus 로고
    • Empirical margin distributions and bounding the generalization error of combined classifiers
    • V. Koltchinskii and D. Panchenko. Empirical margin distributions and bounding the generalization error of combined classifiers. Annals of Statistics, 30, 2002.
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    • Koltchinskii, V.1    Panchenko, D.2
  • 15
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  • 17
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    • Generalization performance of classifiers in terms of observed covering numbers
    • H. U. Simon P. Fischer, editor, Computational Learning Theory: Proceedings of the Fourth European Conference, EuroCOLT'99, Springer, Berlin
    • J. Shawe-Taylor and R.C. Williamson. Generalization performance of classifiers in terms of observed covering numbers. In H. U. Simon P. Fischer, editor, Computational Learning Theory: Proceedings of the Fourth European Conference, EuroCOLT'99, pages 153-167. Springer, Berlin, 1999. Lecture Notes in Artificial Intelligence 1572.
    • (1999) Lecture Notes in Artificial Intelligence , vol.1572 , pp. 153-167
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.