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Volumn , Issue , 2005, Pages 873-880

Unifying the error-correcting and output-code AdaBoost within the margin framework

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COSTS; DATABASE SYSTEMS; OPTIMIZATION;

EID: 31844448666     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (21)

References (15)
  • 1
    • 24044435942 scopus 로고    scopus 로고
    • Reducing multiclass to binary: A unifying approach for margin classifiers
    • Allwein, E. L., Schapire, R. E., & Singer, Y. (2000). Reducing multiclass to binary: A unifying approach for margin classifiers. J. Machine Learning Research, 1, 113-141.
    • (2000) J. Machine Learning Research , vol.1 , pp. 113-141
    • Allwein, E.L.1    Schapire, R.E.2    Singer, Y.3
  • 3
    • 0000275022 scopus 로고    scopus 로고
    • Prediction games and arcing algorithms
    • Breiman, L. (1999). Prediction games and arcing algorithms. Neural Computation, 11, 1493-1517.
    • (1999) Neural Computation , vol.11 , pp. 1493-1517
    • Breiman, L.1
  • 4
    • 0008965347 scopus 로고    scopus 로고
    • On the learnability and design of output codes for multiclass problems
    • Crammer, K., & Singer, Y. (2000). On the learnability and design of output codes for multiclass problems. Computational Learing Theory (pp. 35-46).
    • (2000) Computational Learing Theory , pp. 35-46
    • Crammer, K.1    Singer, Y.2
  • 5
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • Dietterich, T. G. (2000). An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Machine Learning, 40, 139-157.
    • (2000) Machine Learning , vol.40 , pp. 139-157
    • Dietterich, T.G.1
  • 6
    • 0000406788 scopus 로고
    • Solving multiclass learning problems via error-correcting output codes
    • Dietterich, T. G., & Bakiri, G. (1995). Solving multiclass learning problems via error-correcting output codes. J. Artificial Intelligence Research, 2, 263-286.
    • (1995) J. Artificial Intelligence Research , vol.2 , pp. 263-286
    • Dietterich, T.G.1    Bakiri, G.2
  • 7
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • Friedman, J. (2001). Greedy function approximation: a gradient boosting machine. The Annals of Statistics, 29, 1189-1232.
    • (2001) The Annals of Statistics , vol.29 , pp. 1189-1232
    • Friedman, J.1
  • 8
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • Friedman, J., Hastie, T., & Tibshirani, R. (2000). Additive logistic regression: a statistical view of boosting. The Annals of Statistics, 28, 337-407.
    • (2000) The Annals of Statistics , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 10
  • 11
    • 0002550596 scopus 로고    scopus 로고
    • Functional gradient techniques for combining hypotheses
    • B. Scholkopf, A. Smola, P. Bartlett and D. Schuurmans (Eds.). MIT Press
    • Mason, L., Bartlett, J., Baxter, P., & Frean, M. (2000). Functional gradient techniques for combining hypotheses. In B. Scholkopf, A. Smola, P. Bartlett and D. Schuurmans (Eds.), Advances in Large Margin Classifiers, 221-247. MIT Press.
    • (2000) Advances in Large Margin Classifiers , pp. 221-247
    • Mason, L.1    Bartlett, J.2    Baxter, P.3    Frean, M.4
  • 14
    • 0000040021 scopus 로고    scopus 로고
    • Using output codes to boost multiclass learning problems
    • Nashville, TN, USA
    • Schapire, R. E. (1997). Using output codes to boost multiclass learning problems. Proc. 14th Int'l Conf. Machine Learning (pp. 313-321). Nashville, TN, USA.
    • (1997) Proc. 14th Int'l Conf. Machine Learning , pp. 313-321
    • Schapire, R.E.1
  • 15
    • 0032280519 scopus 로고    scopus 로고
    • Boosting the margin: A new explanation for the effectiveness of voting methods
    • Schapire, R. E., Freund, Y., Bartlett, P., & Lee, W. S. (1998). Boosting the margin: a new explanation for the effectiveness of voting methods. The Annals of Statistics, 26, 1651-1686.
    • (1998) The Annals of Statistics , vol.26 , pp. 1651-1686
    • Schapire, R.E.1    Freund, Y.2    Bartlett, P.3    Lee, W.S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.