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Volumn 74, Issue 5, 2011, Pages 680-688

Statistical approaches to combining binary classifiers for multi-class classification

Author keywords

Combining binary classifiers; Group lasso; Meta learning; Multi class classification; Stacking

Indexed keywords

COMBINING BINARY CLASSIFIERS; GROUP LASSO; METALEARNING; MULTI-CLASS CLASSIFICATION; STACKING;

EID: 78650718992     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2010.09.004     Document Type: Article
Times cited : (18)

References (43)
  • 2
    • 22044453925 scopus 로고    scopus 로고
    • The combination of text classifiers using reliability indicators
    • Bennett P.N., Dumais S.T., Horvitz E. The combination of text classifiers using reliability indicators. Information Retrieval 2005, 8:67-100.
    • (2005) Information Retrieval , vol.8 , pp. 67-100
    • Bennett, P.N.1    Dumais, S.T.2    Horvitz, E.3
  • 3
    • 78650743703 scopus 로고    scopus 로고
    • UCI repository of machine learning databases, Technical Report, Department of Information Computational Science, University of California, Irvine
    • C.L. Blake, C.J. Merz, UCI repository of machine learning databases, Technical Report, Department of Information Computational Science, University of California, Irvine, 1998.
    • (1998)
    • Blake, C.L.1    Merz, C.J.2
  • 4
    • 0001667583 scopus 로고
    • Rank analysis of incomplete block designs: I. The methods of paired comparisons
    • Bradley R.A., Terry M.E. Rank analysis of incomplete block designs: I. The methods of paired comparisons. Biometrika 1952, 39:324-345.
    • (1952) Biometrika , vol.39 , pp. 324-345
    • Bradley, R.A.1    Terry, M.E.2
  • 6
    • 0030196364 scopus 로고    scopus 로고
    • Stacked regressions
    • Breiman L. Stacked regressions. Machine Learning 1996, 24:49-64.
    • (1996) Machine Learning , vol.24 , pp. 49-64
    • Breiman, L.1
  • 8
    • 0000761229 scopus 로고
    • Multicategory classification by support vector machines
    • Cortes C., Vapnik V. Multicategory classification by support vector machines. Machine Learning 1995, 12:273-297.
    • (1995) Machine Learning , vol.12 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 9
    • 0010442827 scopus 로고    scopus 로고
    • On the algorithmic implementation of multiclass kernel-based vector machines
    • Crammer K., Singer Y. On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research 2001, 2:265-292.
    • (2001) Journal of Machine Learning Research , vol.2 , pp. 265-292
    • Crammer, K.1    Singer, Y.2
  • 10
    • 0036568032 scopus 로고    scopus 로고
    • On the learnability and design of output codes for multiclass problems
    • Crammer K., Singer Y. On the learnability and design of output codes for multiclass problems. Machine Learning 2002, 47:201-233.
    • (2002) Machine Learning , vol.47 , pp. 201-233
    • Crammer, K.1    Singer, Y.2
  • 13
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • Demšar J. Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research 2006, 7:1-30.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1-30
    • Demšar, J.1
  • 15
    • 26444573178 scopus 로고    scopus 로고
    • Which is the best multiclass SVM method? An empirical study, in: Multiple Classifier Systems
    • K. Duan, S.S. Keerthi, Which is the best multiclass SVM method? An empirical study, in: Multiple Classifier Systems, 2005, pp. 278-285.
    • (2005) , pp. 278-285
    • Duan, K.1    Keerthi, S.S.2
  • 16
    • 12144288329 scopus 로고    scopus 로고
    • Is combining classifiers with stacking better than selecting the best one?
    • Džeroski S., Ženko B. Is combining classifiers with stacking better than selecting the best one?. Machine Learning 2004, 54:255-273.
    • (2004) Machine Learning , vol.54 , pp. 255-273
    • Ďeroski, S.1    Ženko, B.2
  • 17
    • 78650744581 scopus 로고    scopus 로고
    • Another approach to polychotomous classification, Technical Report, Department of Statistics, Stanford University
    • J. Friedman, Another approach to polychotomous classification, Technical Report, Department of Statistics, Stanford University, 1996.
    • (1996)
    • Friedman, J.1
  • 18
    • 0034541162 scopus 로고    scopus 로고
    • Cascade generalization
    • Gama J., Brazdil P. Cascade generalization. Machine Learning 2000, 41:315-343.
    • (2000) Machine Learning , vol.41 , pp. 315-343
    • Gama, J.1    Brazdil, P.2
  • 19
  • 20
    • 0036505670 scopus 로고    scopus 로고
    • A comparison of methods for multiclass support vector machines
    • Hsu C.W., Lin C.J. A comparison of methods for multiclass support vector machines. IEEE Transactions on Neural Networks 2002, 13:415-425.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , pp. 415-425
    • Hsu, C.W.1    Lin, C.J.2
  • 21
    • 30744476239 scopus 로고    scopus 로고
    • Generalized Bradley-Terry models and multi-class probability estimates
    • Huang T.K., Weng R.C., Lin C.J. Generalized Bradley-Terry models and multi-class probability estimates. Journal of Machine Learning Research 2006, 7:85-115.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 85-115
    • Huang, T.K.1    Weng, R.C.2    Lin, C.J.3
  • 25
    • 2142775432 scopus 로고    scopus 로고
    • Multicategory support vector machines: theory and application to the classification of microarray data and satellite radiance data
    • Lee Y., Lin Y., Wahba G. Multicategory support vector machines: theory and application to the classification of microarray data and satellite radiance data. Journal of the American Statistical Association 2004, 99:67-81.
    • (2004) Journal of the American Statistical Association , vol.99 , pp. 67-81
    • Lee, Y.1    Lin, Y.2    Wahba, G.3
  • 28
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • MIT Press
    • Platt J.C. Fast training of support vector machines using sequential minimal optimization. Advances in Kernel Methods-Support Vector Learning 1999, 185-208. MIT Press.
    • (1999) Advances in Kernel Methods-Support Vector Learning , pp. 185-208
    • Platt, J.C.1
  • 29
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • MIT Press
    • Platt J.C. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Advances in Large Margin Classifiers 1999, 61-74. MIT Press.
    • (1999) Advances in Large Margin Classifiers , pp. 61-74
    • Platt, J.C.1
  • 33
    • 78650748459 scopus 로고    scopus 로고
    • Multiclass classification as a decoding problem, in: Proceedings of the 9th Workshop on Information-Based Induction Sciences(in Japanese).
    • T. Takenouchi, S. Ishii, Multiclass classification as a decoding problem, in: Proceedings of the 9th Workshop on Information-Based Induction Sciences, 2006, pp. 244-249 (in Japanese).
    • (2006) , pp. 244-249
    • Takenouchi, T.1    Ishii, S.2
  • 34
    • 34249062309 scopus 로고    scopus 로고
    • On the consistency of multiclass classification methods
    • Tewari A., Bartlett P. On the consistency of multiclass classification methods. Journal of Machine Learning Research 2007, 8:1007-1025.
    • (2007) Journal of Machine Learning Research , vol.8 , pp. 1007-1025
    • Tewari, A.1    Bartlett, P.2
  • 36
    • 0037365188 scopus 로고    scopus 로고
    • Combining classifiers with meta decision trees
    • Todorovski L., Džeroski S. Combining classifiers with meta decision trees. Machine Learning 2003, 50:223-249.
    • (2003) Machine Learning , vol.50 , pp. 223-249
    • Todorovski, L.1    Džeroski, S.2
  • 37
    • 78650721561 scopus 로고    scopus 로고
    • Multi-class support vector machines, Technical Report, Department of Computer Science, University of London
    • J. Weston, C. Watkins, Multi-class support vector machines, Technical Report, Department of Computer Science, University of London, 1998.
    • (1998)
    • Weston, J.1    Watkins, C.2
  • 38
    • 0026692226 scopus 로고
    • Stacked generalization
    • Wolpert D.H. Stacked generalization. Neural Networks 1992, 5:241-259.
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.H.1
  • 39
    • 78650717818 scopus 로고    scopus 로고
    • Combining stacking with bagging to improve a learning algorithm, Technical Report, Santa Fe Institute
    • D.H. Wolpert, W.G. Macready, Combining stacking with bagging to improve a learning algorithm, Technical Report, Santa Fe Institute, 1996.
    • (1996)
    • Wolpert, D.H.1    Macready, W.G.2
  • 40
    • 51349159085 scopus 로고    scopus 로고
    • Probability estimates for multi-class classification by pairwise coupling
    • Wu T.F., Lin C.J., Weng R.C. Probability estimates for multi-class classification by pairwise coupling. Journal of Machine Learning Research 2004, 5:975-1005.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 975-1005
    • Wu, T.F.1    Lin, C.J.2    Weng, R.C.3
  • 42
    • 26944483874 scopus 로고    scopus 로고
    • Statistical analysis of some multi-category large margin classification methods
    • Zhang T. Statistical analysis of some multi-category large margin classification methods. Journal of Machine Learning Research 2004, 5:1225-1251.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 1225-1251
    • Zhang, T.1


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