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Volumn 7, Issue 1, 2012, Pages 127-133

Boosting and margin theory

Author keywords

boosting; explanation; generalization; margin

Indexed keywords


EID: 84862820587     PISSN: 16733460     EISSN: 16733584     Source Type: Journal    
DOI: 10.1007/s11460-012-0188-9     Document Type: Article
Times cited : (6)

References (17)
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    • Freund, Y.1    Schapire, R.E.2
  • 3
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    • Arcing classifiers
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    • Breiman, L.1
  • 5
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    • Boosting the margin: A new explanation for the effectiveness of voting methods
    • Schapire R E, Freund Y, Bartlett P, Lee W. Boosting the margin: A new explanation for the effectiveness of voting methods. Annals of Statistics, 1998, 26(5): 1651-1686.
    • (1998) Annals of Statistics , vol.26 , Issue.5 , pp. 1651-1686
    • Schapire, R.E.1    Freund, Y.2    Bartlett, P.3    Lee, W.4
  • 6
    • 0000275022 scopus 로고    scopus 로고
    • Prediction games and arcing algorithms
    • Breiman L. Prediction games and arcing algorithms. Neural Computation, 1999, 11(7): 1493-1517.
    • (1999) Neural Computation , vol.11 , Issue.7 , pp. 1493-1517
    • Breiman, L.1
  • 11
    • 0036104545 scopus 로고    scopus 로고
    • Empirical margin distributions and bounding the generalization error of combined classifiers
    • Koltchinskii V, Panchenko D. Empirical margin distributions and bounding the generalization error of combined classifiers. Annals of Statistics, 2002, 30(1): 1-50.
    • (2002) Annals of Statistics , vol.30 , Issue.1 , pp. 1-50
    • Koltchinskii, V.1    Panchenko, D.2
  • 12
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    • Complexities of convex combinations and bounding the generalization error in classification
    • Koltchinskii V, Panchenko D. Complexities of convex combinations and bounding the generalization error in classification. Annals of Statistics, 2005, 33(4): 1455-1496.
    • (2005) Annals of Statistics , vol.33 , Issue.4 , pp. 1455-1496
    • Koltchinskii, V.1    Panchenko, D.2
  • 14
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    • Tutorial on practical prediction theory for classification
    • Langford J. Tutorial on practical prediction theory for classification. Journal of Machine Learning Research, 2005, 6: 273-306.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 273-306
    • Langford, J.1
  • 15
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    • UCI machine learning repository
    • Asuncion A, Newman D J. UCI machine learning repository. 2007, http://www. ics. uci. edu/?mlearn/MLRepository. html.
    • (2007)
    • Asuncion, A.1    Newman, D.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.