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Volumn 5589 LNAI, Issue , 2009, Pages 397-404

A novel multimodal probability model for cluster analysis

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANALYSIS; DATA SETS; FUZZY C MEAN; MAXIMUM LIKELIHOOD METHODS; MIXTURE DISTRIBUTIONS; MULTI-MODAL; POSSIBILISTIC C-MEANS; PROBABILITY DISTRIBUTION MODEL; PROBABILITY MODELS;

EID: 69049105540     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02962-2_50     Document Type: Conference Paper
Times cited : (3)

References (16)
  • 2
    • 0017826298 scopus 로고
    • Asymptotic behavior of classification maximum likelihood estimates
    • Bryant, P.G., Williamson, J.A.: Asymptotic behavior of classification maximum likelihood estimates. Biometrica 65, 273-438 (1978)
    • (1978) Biometrica , vol.65 , pp. 273-438
    • Bryant, P.G.1    Williamson, J.A.2
  • 3
    • 0000306608 scopus 로고
    • Clustering criteria for discrete data and latent class models
    • Celeux, G., Govaert, G.: Clustering criteria for discrete data and latent class models. Journal of classification 8, 157-176 (1991)
    • (1991) Journal of classification , vol.8 , pp. 157-176
    • Celeux, G.1    Govaert, G.2
  • 4
    • 0016421071 scopus 로고
    • The estimation of the gradient of a density function, with applications in pattern recognition
    • Fukunaga, K., Hostetler, L.D.: The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Trans. Information Theory 21, 32-40 (1975)
    • (1975) IEEE Trans. Information Theory , vol.21 , pp. 32-40
    • Fukunaga, K.1    Hostetler, L.D.2
  • 8
    • 0001457509 scopus 로고
    • Some methods for classification and analysis of multivariate observations
    • University of California Press, Berkley
    • MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proc. of 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281-297. University of California Press, Berkley (1967)
    • (1967) Proc. of 5th Berkeley Symposium on Mathematical Statistics and Probability , vol.1 , pp. 281-297
    • MacQueen, J.1
  • 10
    • 0001340183 scopus 로고
    • Clustering methods based on likelihood ration criteria
    • Scott, A.J., Symons, M.J.: Clustering methods based on likelihood ration criteria. Biometrics 27, 387-397 (1971)
    • (1971) Biometrics , vol.27 , pp. 387-397
    • Scott, A.J.1    Symons, M.J.2
  • 11
    • 0002757023 scopus 로고    scopus 로고
    • Probability models and hypotheses testing in partitioning cluster analysis
    • Arabie, P, Hubert, L.J, Soete, G.D, eds, World Scientific Publ, River Edge
    • Bock, H.H.: Probability models and hypotheses testing in partitioning cluster analysis. In: Arabie, P., Hubert, L.J., Soete, G.D. (eds.) Clustering and Classification, pp. 377-453. World Scientific Publ., River Edge (1996)
    • (1996) Clustering and Classification , pp. 377-453
    • Bock, H.H.1
  • 12
    • 0001641730 scopus 로고
    • On a class of fuzzy classification maximum likelihood procedures
    • Yang, M.S.: On a class of fuzzy classification maximum likelihood procedures. Fuzzy Sets and Systems 57, 365-375 (1993)
    • (1993) Fuzzy Sets and Systems , vol.57 , pp. 365-375
    • Yang, M.S.1
  • 15
    • 69049098734 scopus 로고
    • Statistical models for cluster analysis
    • Diday, E, Lechevallier, Y, eds, Commack, pp, Nova Science, New York
    • Windham, M.P.: Statistical models for cluster analysis. In: Diday, E., Lechevallier, Y. (eds.) Symbolic-numeric data analysis and learning, Commack, pp. 17-26. Nova Science, New York (1991)
    • (1991) Symbolic-numeric data analysis and learning , pp. 17-26
    • Windham, M.P.1
  • 16
    • 69049119033 scopus 로고
    • Clustering model and metric with continuous data
    • Diday, E, ed, Commack, pp, Nova Science, New York
    • Govaert, G.: Clustering model and metric with continuous data. In: Diday, E. (ed.) Learning symbolic and numeric knowledge, Commack, pp. 95-102. Nova Science, New York (1989)
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    • Govaert, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.