메뉴 건너뛰기




Volumn 118, Issue , 2013, Pages 101-114

Double-base asymmetric AdaBoost

Author keywords

AdaBoost; Asymmetry; Boosting; Classification; Cost

Indexed keywords

ASYMMETRY; BOOSTING; COMPUTATIONAL ADVANTAGES; COST-SENSITIVE; COST-SENSITIVE ADABOOST; SEARCH PROCEDURES; THEORETICAL DERIVATIONS; WEAK CLASSIFIERS;

EID: 84881250403     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.02.019     Document Type: Article
Times cited : (12)

References (28)
  • 1
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • Schapire R. The strength of weak learnability. Mach. Learn. 1990, 5:197-227.
    • (1990) Mach. Learn. , vol.5 , pp. 197-227
    • Schapire, R.1
  • 2
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Freund Y., Schapire R. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 1997, 55:119-139.
    • (1997) J. Comput. Syst. Sci. , vol.55 , pp. 119-139
    • Freund, Y.1    Schapire, R.2
  • 3
    • 0032280519 scopus 로고    scopus 로고
    • Boosting the margin. a new explanation for the effectiveness of voting methods
    • Schapire R., Freund Y., Bartlett P., Lee W. Boosting the margin. a new explanation for the effectiveness of voting methods. Ann. Stat. 1998, 26:1651-1686.
    • (1998) Ann. Stat. , vol.26 , pp. 1651-1686
    • Schapire, R.1    Freund, Y.2    Bartlett, P.3    Lee, W.4
  • 4
    • 0033281701 scopus 로고    scopus 로고
    • Improved boosting algorithms using confidence-rated predictions
    • Schapire R., Singer Y. Improved boosting algorithms using confidence-rated predictions. Mach. Learn. 1999, 37:297-336.
    • (1999) Mach. Learn. , vol.37 , pp. 297-336
    • Schapire, R.1    Singer, Y.2
  • 5
    • 0000551189 scopus 로고    scopus 로고
    • Popular ensemble methods. an empirical study
    • Opitz D., Maclin R. Popular ensemble methods. an empirical study. J. Artif. Intell. Res. 1999, 11:169-198.
    • (1999) J. Artif. Intell. Res. , vol.11 , pp. 169-198
    • Opitz, D.1    Maclin, R.2
  • 6
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression. a statistical view of boosting
    • Friedman J., Hastie T., Tibshirani R. Additive logistic regression. a statistical view of boosting. Ann. Stat. 2000, 28:337-407.
    • (2000) Ann. Stat. , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 7
    • 41549131613 scopus 로고    scopus 로고
    • Evidence contrary to the statistical view of boosting
    • Mease D., Wyner A. Evidence contrary to the statistical view of boosting. J. Mach. Learn. Res. 2008, 9:175-194.
    • (2008) J. Mach. Learn. Res. , vol.9 , pp. 175-194
    • Mease, D.1    Wyner, A.2
  • 8
    • 2142812371 scopus 로고    scopus 로고
    • Robust real-time face detection
    • Viola P., Jones M. Robust real-time face detection. Int. J. Comput. Vision 2004, 57:137-154.
    • (2004) Int. J. Comput. Vision , vol.57 , pp. 137-154
    • Viola, P.1    Jones, M.2
  • 10
    • 84867577175 scopus 로고    scopus 로고
    • The foundations of cost-sensitive learning
    • Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence
    • C. Elkan, The foundations of cost-sensitive learning, in: Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001, pp. 973-978.
    • (2001) , pp. 973-978
    • Elkan, C.1
  • 11
    • 1442275185 scopus 로고    scopus 로고
    • Learning when training data are costly. the effect of class distribution on tree induction
    • Weiss G., Provost F. Learning when training data are costly. the effect of class distribution on tree induction. J. Artif. Intell. Res. 2003, 19:315-354.
    • (2003) J. Artif. Intell. Res. , vol.19 , pp. 315-354
    • Weiss, G.1    Provost, F.2
  • 12
    • 84899002132 scopus 로고    scopus 로고
    • Optimizing classifiers for imbalanced training sets
    • Advances in Neural Information Processing Systems
    • G. Karakoulas, J. Shawe-Taylor, Optimizing classifiers for imbalanced training sets, in: Advances in Neural Information Processing Systems, vol. 12, 1999, pp. 253-259.
    • (1999) , vol.12 , pp. 253-259
    • Karakoulas, G.1    Shawe-Taylor, J.2
  • 13
    • 0013316935 scopus 로고    scopus 로고
    • AdaCost: misclassification cost-sensitive boosting
    • Proceedings of the 16th International Conference on Machine Learning
    • W. Fan, S. Stolfo, J. Zhang, P. Chan, AdaCost: misclassification cost-sensitive boosting, in: Proceedings of the 16th International Conference on Machine Learning, 1999, pp. 97-105.
    • (1999) , pp. 97-105
    • Fan, W.1    Stolfo, S.2    Zhang, J.3    Chan, P.4
  • 14
    • 0002804620 scopus 로고    scopus 로고
    • A comparative study of cost-sensitive boosting algorithms
    • Proceedings of the 17th International Conference on Machine Learning
    • K. Ting, A comparative study of cost-sensitive boosting algorithms, in: Proceedings of the 17th International Conference on Machine Learning, 2000, pp. 983-990.
    • (2000) , pp. 983-990
    • Ting, K.1
  • 15
    • 2442516613 scopus 로고    scopus 로고
    • Fast and robust classification using asymmetric AdaBoost and a detector cascade
    • Advances in Neural Information Processing Systems
    • P. Viola, M. Jones, Fast and robust classification using asymmetric AdaBoost and a detector cascade, in: Advances in Neural Information Processing Systems, vol. 14, 2001.
    • (2001) , vol.14
    • Viola, P.1    Jones, M.2
  • 16
    • 34547673383 scopus 로고    scopus 로고
    • Cost-sensitive boosting for classification of imbalanced data
    • Sun Y., Kamel M., Wong A., Wang Y. Cost-sensitive boosting for classification of imbalanced data. Pattern Recognition 2007, 40:3358-3378.
    • (2007) Pattern Recognition , vol.40 , pp. 3358-3378
    • Sun, Y.1    Kamel, M.2    Wong, A.3    Wang, Y.4
  • 18
    • 84881233917 scopus 로고    scopus 로고
    • Asymmetric boosting, in: Proceedings of the 24th International Conference on Machine Learning
    • H. Masnadi-Shirazi, N. Vasconcelos, Asymmetric boosting, in: Proceedings of the 24th International Conference on Machine Learning.
    • Masnadi-Shirazi, H.1    Vasconcelos, N.2
  • 19
    • 83455195511 scopus 로고    scopus 로고
    • Shedding light on the asymmetric learning capability of AdaBoost
    • Landesa-Vázquez I., Alba-Castro J. Shedding light on the asymmetric learning capability of AdaBoost. Pattern Recognition Lett. 2012, 33:247-255.
    • (2012) Pattern Recognition Lett. , vol.33 , pp. 247-255
    • Landesa-Vázquez, I.1    Alba-Castro, J.2
  • 21
    • 85101511266 scopus 로고    scopus 로고
    • Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions
    • Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, AAAI Press
    • F. Provost, T. Fawcett, Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions, in: Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, AAAI Press, 1997, pp. 43-48.
    • (1997) , pp. 43-48
    • Provost, F.1    Fawcett, T.2
  • 22
    • 33646023117 scopus 로고    scopus 로고
    • An introduction to ROC analysis
    • Fawcett T. An introduction to ROC analysis. Pattern Recognition Lett. 2006, 27:861-874.
    • (2006) Pattern Recognition Lett. , vol.27 , pp. 861-874
    • Fawcett, T.1
  • 23
    • 0034592774 scopus 로고    scopus 로고
    • Explicitly representing expected cost: an alternative to ROC representation
    • Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '00, ACM
    • C. Drummond, R. Holte, Explicitly representing expected cost: an alternative to ROC representation, in: Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '00, ACM, 2000, pp. 198-207.
    • (2000) , pp. 198-207
    • Drummond, C.1    Holte, R.2
  • 24
    • 84881234019 scopus 로고    scopus 로고
    • UCI Machine Learning Repository
    • A. Frank, A. Asuncion, UCI Machine Learning Repository, 2010.
    • (2010)
    • Frank, A.1    Asuncion, A.2
  • 25
    • 0038975426 scopus 로고
    • Finding a zero by means of successive linear interpolation
    • Wiley Interscience, B. Dejon, P. Henrici (Eds.)
    • Dekker T.J. Finding a zero by means of successive linear interpolation. Constructive Aspects of the Fundamental Theorem of Algebra 1969, 37-48. Wiley Interscience. B. Dejon, P. Henrici (Eds.).
    • (1969) Constructive Aspects of the Fundamental Theorem of Algebra , pp. 37-48
    • Dekker, T.J.1
  • 27
    • 0003941277 scopus 로고    scopus 로고
    • Face detection in still gray images
    • A.I. memo 1687, Center for Biological and Computational Learning, MIT, Cambridge, MA
    • B. Heisele, T. Poggio, M. Pontil, Face detection in still gray images, A.I. memo 1687, Center for Biological and Computational Learning, MIT, Cambridge, MA, 2000.
    • (2000)
    • Heisele, B.1    Poggio, T.2    Pontil, M.3
  • 28
    • 23944455002 scopus 로고    scopus 로고
    • An empirical comparison of SNoW and SVMs for face detection
    • A.I. memo 2001-004, Center for Biological and Computational Learning, MIT, Cambridge, MA
    • M. Alvira, R. Rifkin, An empirical comparison of SNoW and SVMs for face detection, A.I. memo 2001-004, Center for Biological and Computational Learning, MIT, Cambridge, MA, 2001.
    • (2001)
    • Alvira, M.1    Rifkin, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.