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Volumn 4472 LNCS, Issue , 2007, Pages 312-321

Modelling multiple-classifier relationships using Bayesian belief networks

Author keywords

Bayesian belief networks; Diversity; Multiple classifier systems

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA STRUCTURES; ENGINEERING RESEARCH; MATHEMATICAL MODELS; STRUCTURED PROGRAMMING;

EID: 37249057783     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72523-7_32     Document Type: Conference Paper
Times cited : (3)

References (24)
  • 1
    • 0037403516 scopus 로고    scopus 로고
    • Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy
    • Kuncheva, L.I. and C.J. Whitaker, Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. Machine Learning, 2003. 51(2): p. 181-207.
    • (2003) Machine Learning , vol.51 , Issue.2 , pp. 181-207
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 5
    • 37249028076 scopus 로고    scopus 로고
    • Chindaro, S., K. Sirlantzis, and M.C. Fairhurst. Analysis and Modelling of Diversity Contribution to Ensemble-Based Texture Recognition Performance. in Proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005. 2005. Seaside, California, USA: LNCS 3541.
    • Chindaro, S., K. Sirlantzis, and M.C. Fairhurst. Analysis and Modelling of Diversity Contribution to Ensemble-Based Texture Recognition Performance. in Proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005. 2005. Seaside, California, USA: LNCS 3541.
  • 6
    • 0036501674 scopus 로고    scopus 로고
    • Generating classifier outputs of fixed accuracy and diversity
    • Kuncheva, L. and R. Kountch, Generating classifier outputs of fixed accuracy and diversity. Pattern Recognition Letters, 2002. 23: p. 593-600.
    • (2002) Pattern Recognition Letters , vol.23 , pp. 593-600
    • Kuncheva, L.1    Kountch, R.2
  • 7
    • 0011187879 scopus 로고    scopus 로고
    • Multiple Classifier Combination: Lessons and Next Steps
    • World Scientific
    • Ho, T.K., Multiple Classifier Combination: Lessons and Next Steps. Hybrid Methods in Pattern Recognition; World Scientific, 2002: p. 171-198.
    • (2002) Hybrid Methods in Pattern Recognition , pp. 171-198
    • Ho, T.K.1
  • 8
    • 0036173326 scopus 로고    scopus 로고
    • A Bayesian Framework for Combining Gene Predictions
    • Pavlovic, V., A. Garg, and S. Kasif, A Bayesian Framework for Combining Gene Predictions. Biinformatics, 2002. 1: p. 19-27.
    • (2002) Biinformatics , vol.1 , pp. 19-27
    • Pavlovic, V.1    Garg, A.2    Kasif, S.3
  • 10
    • 0004283231 scopus 로고    scopus 로고
    • Dordrecht, The Netherlands: Kluwer Academic
    • Jordan, M.I., Learning Graphical Models. 1996, Dordrecht, The Netherlands: Kluwer Academic.
    • (1996) Learning Graphical Models
    • Jordan, M.I.1
  • 11
    • 34249832377 scopus 로고
    • A Bayesian Method for the induction of probabilistic networks from data
    • Cooper., G.F. and E. Herskovits, A Bayesian Method for the induction of probabilistic networks from data. Machine Learning, 1992. 9: p. 309-347.
    • (1992) Machine Learning , vol.9 , pp. 309-347
    • Cooper, G.F.1    Herskovits, E.2
  • 12
    • 0004193705 scopus 로고
    • Computer-based probabilistic network construction
    • Doctoral dissertation, Stanford University, Stanford, CA
    • Herskovits, E.H., Computer-based probabilistic network construction. Medical information sciences, Doctoral dissertation., 1991. Stanford University, Stanford, CA.
    • (1991) Medical information sciences
    • Herskovits, E.H.1
  • 13
    • 0008564212 scopus 로고    scopus 로고
    • Learning Bayesian belief networks based on the MDL principle: An efficient algorithm using the branch and bound technique
    • Bally, Italy
    • Suzuki, J. Learning Bayesian belief networks based on the MDL principle: An efficient algorithm using the branch and bound technique. in Proceedings of the international conference on machine learning, 1996. 1996. Bally, Italy.
    • (1996) Proceedings of the international conference on machine learning
    • Suzuki, J.1
  • 14
    • 37249056930 scopus 로고    scopus 로고
    • R.M. Fung, R.M. and S.L. Crawford. Constructor: a system for the induction of probabilistic models, in Proceedings of AAAI Boston, MA, MIT Press
    • R.M. Fung, R.M. and S.L. Crawford. Constructor: a system for the induction of probabilistic models.. in Proceedings of AAAI Boston, MA.: MIT Press.
  • 15
    • 0008576772 scopus 로고
    • Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information
    • Amsterdam: North-Holland
    • Srinivas, S., S. Russell, and A. Agogino. Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information. in Uncertainty in artificial intelligence 5. 1990. Amsterdam: North-Holland.
    • (1990) Uncertainty in artificial intelligence , vol.5
    • Srinivas, S.1    Russell, S.2    Agogino, A.3
  • 16
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • Heckerman, D., D. Geiger, and D.Chickering, Learning Bayesian networks: The combination of knowledge and statistical data.. Machine Learning, 1995. 20: p. 197-243.
    • (1995) Machine Learning , vol.20 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.3
  • 17
    • 37249006176 scopus 로고    scopus 로고
    • Duin, R.P.W., et al., PRTools 4, A Matlab Toolbox for Pattern Recognition, Delft University of Technology. 2004.
    • Duin, R.P.W., et al., PRTools 4, "A Matlab Toolbox for Pattern Recognition", Delft University of Technology. 2004.
  • 18
    • 33745834241 scopus 로고    scopus 로고
    • UCI:, University of California, Irvine, Dept. of Inform. and Comp. Sc
    • UCI: Repository of machine learning databases, [http://www.ics.uci.edu/ ~mlearn/MLRepository.html],. University of California, Irvine, Dept. of Inform. and Comp. Sc., 1998.
    • (1998) Repository of machine learning databases
  • 20
    • 37249025563 scopus 로고    scopus 로고
    • Yule, G., On the association of attributes in statistics. Phil. Tansaction, 1900. A(194): p. 257-319.
    • Yule, G., On the association of attributes in statistics. Phil. Tansaction, 1900. A(194): p. 257-319.
  • 22
    • 0032139235 scopus 로고    scopus 로고
    • The Random Subspace Method for Constructing Decision Forests
    • Ho, T.K., The Random Subspace Method for Constructing Decision Forests. IEEE Trans on Pattern Analysis and Machine Intelligence, 1998. 20(8): p. 832-844.
    • (1998) IEEE Trans on Pattern Analysis and Machine Intelligence , vol.20 , Issue.8 , pp. 832-844
    • Ho, T.K.1
  • 23
    • 0035420134 scopus 로고    scopus 로고
    • Design of effective neural network ensembles for image classification processes
    • Giacinto, G. and F. Roli, Design of effective neural network ensembles for image classification processes. Image and Vision Computing Journal, 2001. 19(9/10): p. 699-707.
    • (2001) Image and Vision Computing Journal , vol.19 , Issue.9-10 , pp. 699-707
    • Giacinto, G.1    Roli, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.