메뉴 건너뛰기




Volumn 3, Issue 4, 2002, Pages 245-258

An experimental study on diversity for bagging and boosting with linear classifiers

Author keywords

Bagging; Boosting; Combining classifier; Diversity

Indexed keywords

CLASSIFIERS; FUNCTIONS; NEURAL NETWORKS; PROBABILITY; VECTORS;

EID: 0036896235     PISSN: 15662535     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1566-2535(02)00093-3     Document Type: Article
Times cited : (139)

References (37)
  • 1
    • 0032645080 scopus 로고    scopus 로고
    • An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
    • Bauer E., Kohavi R. An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning. 36:1999;105-142.
    • (1999) Machine Learning , vol.36 , pp. 105-142
    • Bauer, E.1    Kohavi, R.2
  • 2
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Machine Learning. 26(2):1996;123-140.
    • (1996) Machine Learning , vol.26 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 3
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • Breiman L. Arcing classifiers. The Annals of Statistics. 26(3):1998;801-849.
    • (1998) The Annals of Statistics , vol.26 , Issue.3 , pp. 801-849
    • Breiman, L.1
  • 4
    • 0001963137 scopus 로고    scopus 로고
    • Combining predictors
    • SharkeyA.J.C. London: Springer-Verlag
    • Breiman L. Combining predictors. Sharkey A.J.C. Combining Artificial Neural Nets. 1999;31-50 Springer-Verlag, London.
    • (1999) Combining Artificial Neural Nets , pp. 31-50
    • Breiman, L.1
  • 6
    • 80053403826 scopus 로고    scopus 로고
    • Ensemble methods in machine learning
    • Kittler J. Roli F. Multiple Classifier Systems, Springer
    • Dietterich T.G. Ensemble methods in machine learning. Kittler J., Roli F. Multiple Classifier Systems. Lecture Notes in Computer Science. vol. 1857:2000;1-15 Springer.
    • (2000) Lecture Notes in Computer Science , vol.1857 , pp. 1-15
    • Dietterich, T.G.1
  • 8
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Freund Y., Schapire R.E. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences. 55(1):1997;119-139.
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 9
    • 0001408126 scopus 로고    scopus 로고
    • Discussion of the paper Arcing Classifiers by Leo Breiman
    • Freund Y., Schapire R.E. Discussion of the paper Arcing Classifiers by Leo Breiman. The Annals of Statistics. 26(3):1998;824-832.
    • (1998) The Annals of Statistics , vol.26 , Issue.3 , pp. 824-832
    • Freund, Y.1    Schapire, R.E.2
  • 10
    • 0035420134 scopus 로고    scopus 로고
    • Design of effective neural network ensembles for image classification processes
    • Giacinto G., Roli F. Design of effective neural network ensembles for image classification processes. Image Vision and Computing Journal. 19(9-10):2001;699-707.
    • (2001) Image Vision and Computing Journal , vol.19 , Issue.9-10 , pp. 699-707
    • Giacinto, G.1    Roli, F.2
  • 16
    • 85054435084 scopus 로고
    • Neural network ensembles, cross validation and active learning
    • TesauroG.TouretzkyD.S.LeenT.K. Cambridge, MA: MIT Press
    • Krogh A., Vedelsby J. Neural network ensembles, cross validation and active learning. Tesauro G., Touretzky D.S., Leen T.K. Advances in Neural Information Processing Systems. vol. 7:1995;231-238 MIT Press, Cambridge, MA.
    • (1995) Advances in Neural Information Processing Systems , vol.7 , pp. 231-238
    • Krogh, A.1    Vedelsby, J.2
  • 17
    • 0035899791 scopus 로고    scopus 로고
    • Using measures of similarity and inclusion for multiple classifier fusion by decision templates
    • Kuncheva L.I. Using measures of similarity and inclusion for multiple classifier fusion by decision templates. Fuzzy Sets and Systems. 122(3):2001;401-407.
    • (2001) Fuzzy Sets and Systems , vol.122 , Issue.3 , pp. 401-407
    • Kuncheva, L.I.1
  • 19
    • 0034830461 scopus 로고    scopus 로고
    • Decision templates for multiple classifier fusion: An experimental comparison
    • Kuncheva L.I., Bezdek J.C., Duin R.P.W. Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognition. 34(2):2001;299-314.
    • (2001) Pattern Recognition , vol.34 , Issue.2 , pp. 299-314
    • Kuncheva, L.I.1    Bezdek, J.C.2    Duin, R.P.W.3
  • 20
    • 6344289532 scopus 로고    scopus 로고
    • Ten measures of diversity in classifier ensembles: Limits for two classifiers
    • Birmingham, IEE
    • Kuncheva L.I., Whitaker C.J. Ten measures of diversity in classifier ensembles: limits for two classifiers. Proc. IEE Workshop on Intelligent Sensor Processing, Birmingham. 2001;10/1-10/6 IEE.
    • (2001) Proc. IEE Workshop on Intelligent Sensor Processing , pp. 101-106
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 23
    • 84867038166 scopus 로고    scopus 로고
    • Classifier combinations: Implementations and theoretical issues
    • Kittler J. Roli F. Multiple Classifier Systems, Springer
    • Lam L. Classifier combinations: implementations and theoretical issues. Kittler J., Roli F. Multiple Classifier Systems. Lecture Notes in Computer Science. vol. 1857:2000;78-86 Springer.
    • (2000) Lecture Notes in Computer Science , vol.1857 , pp. 78-86
    • Lam, L.1
  • 25
    • 0000484635 scopus 로고    scopus 로고
    • Simultaneous learning of negatively correlated neural network
    • Brisbane, Australia
    • Y. Liu, X. Yao, Simultaneous learning of negatively correlated neural network, in: Proc 9th Australian Conference on Neural Networks (ACNN'98), Brisbane, Australia, 1998, pp. 183-187.
    • (1998) Proc 9th Australian Conference on Neural Networks (ACNN'98) , pp. 183-187
    • Liu, Y.1    Yao, X.2
  • 26
    • 0033485370 scopus 로고    scopus 로고
    • Ensemble learning via negative correlation
    • Liu Y., Yao X. Ensemble learning via negative correlation. Neural Networks. 12:1999;1399-1404.
    • (1999) Neural Networks , vol.12 , pp. 1399-1404
    • Liu, Y.1    Yao, X.2
  • 28
    • 0031244715 scopus 로고    scopus 로고
    • Software diversity: Practical statistics for its measurement and exploitation
    • Partridge D., Krzanowski W.J. Software diversity: practical statistics for its measurement and exploitation. Information and Software Technology. 39:1997;707-717.
    • (1997) Information and Software Technology , vol.39 , pp. 707-717
    • Partridge, D.1    Krzanowski, W.J.2
  • 29
    • 0030367578 scopus 로고    scopus 로고
    • Ensemble learning using decorrelated neural networks
    • Rosen B.E. Ensemble learning using decorrelated neural networks. Connection Science. 8(3/4):1996;373-383.
    • (1996) Connection Science , vol.8 , Issue.3-4 , pp. 373-383
    • Rosen, B.E.1
  • 30
    • 84956988905 scopus 로고    scopus 로고
    • Application of the evolutionary algorithms for classifier selection in multiple classifier systems with majority voting
    • Kittler J. Roli F., Proc. Second International Workshop on Multiple Classifier Systems, Springer-Verlag
    • Ruta D., Gabrys B. Application of the evolutionary algorithms for classifier selection in multiple classifier systems with majority voting. Kittler J., Roli F. Proc. Second International Workshop on Multiple Classifier Systems. Lecture Notes in Computer Science. vol. 2096:2001;Springer-Verlag.
    • (2001) Lecture Notes in Computer Science , vol.2096
    • Ruta, D.1    Gabrys, B.2
  • 31
    • 0345143226 scopus 로고    scopus 로고
    • The sources of increased accuracy for two proposed boosting algorithms
    • Integrating Multiple Learned Models Workshop
    • D.B. Skalak, The sources of increased accuracy for two proposed boosting algorithms, in: Proc. American Association for Artificial Intelligence, AAAI-96, Integrating Multiple Learned Models Workshop, 1996.
    • (1996) Proc. American Association for Artificial Intelligence, AAAI-96
    • Skalak, D.B.1
  • 32
    • 0004132023 scopus 로고    scopus 로고
    • Ph.D. thesis, Delft University of Technology, Delft, The Netherlands
    • M. Skurichina, Stabilizing Weak Classifiers, Ph.D. thesis, Delft University of Technology, Delft, The Netherlands, 2001.
    • (2001) Stabilizing Weak Classifiers
    • Skurichina, M.1
  • 34
    • 0030365938 scopus 로고    scopus 로고
    • Error correlation and error reduction in ensemble classifiers
    • Tumer K., Ghosh J. Error correlation and error reduction in ensemble classifiers. Connection Science. 8(3/4):1996;385-404.
    • (1996) Connection Science , vol.8 , Issue.3-4 , pp. 385-404
    • Tumer, K.1    Ghosh, J.2
  • 35
    • 0001562581 scopus 로고    scopus 로고
    • Linear and order statistics combiners for pattern classification
    • SharkeyA.J.C. London: Springer-Verlag
    • Tumer K., Ghosh J. Linear and order statistics combiners for pattern classification. Sharkey A.J.C. Combining Artificial Neural Nets. 1999;127-161 Springer-Verlag, London.
    • (1999) Combining Artificial Neural Nets , pp. 127-161
    • Tumer, K.1    Ghosh, J.2
  • 36
    • 0026860706 scopus 로고
    • Methods of combining multiple classifiers and their application to handwriting recognition
    • Xu L., Krzyzak A., Suen C.Y. Methods of combining multiple classifiers and their application to handwriting recognition. IEEE Transactions on Systems, Man, and Cybernetics. 22:1992;418-435.
    • (1992) IEEE Transactions on Systems, Man, and Cybernetics , vol.22 , pp. 418-435
    • Xu, L.1    Krzyzak, A.2    Suen, C.Y.3
  • 37
    • 0001218846 scopus 로고
    • On the association of attributes in statistics
    • Yule G.U. On the association of attributes in statistics. Philos. Trans., A. 194:1900;257-319.
    • (1900) Philos. Trans., A , vol.194 , pp. 257-319
    • Yule, G.U.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.