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Volumn , Issue , 2008, Pages 127-138

The noise component in model-based cluster analysis

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; INFORMATION ANALYSIS; MACHINE LEARNING; MIXTURES;

EID: 84879562466     PISSN: 14318814     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-78246-9_16     Document Type: Conference Paper
Times cited : (19)

References (12)
  • 1
    • 0027453616 scopus 로고
    • Model-based gaussian and non-gaussian clustering
    • BANFIELD, J. D. and RAFTERY, A. E. (1993): Model-Based Gaussian and Non-Gaussian Clustering. Biometrics, 49, 803-821
    • (1993) Biometrics , vol.49 , pp. 803-821
    • Banfield, J.D.1    Raftery, A.E.2
  • 2
    • 0008535006 scopus 로고
    • Mixture models and atypical values
    • CAMPBELL, N. A. (1984): Mixture models and atypical values. Mathematical Geology, 16, 465-477.
    • (1984) Mathematical Geology , vol.16 , pp. 465-477
    • Campbell, N.A.1
  • 3
    • 84879569613 scopus 로고    scopus 로고
    • Identifiability for mixtures of distributions from a location-scale family with uniforms
    • University of Salerno
    • CORETTO P. and HENNIG C. (2006): Identifiability for mixtures of distributions from a location-scale family with uniforms. DISES Working Papers No. 3.186, University of Salerno.
    • (2006) DISES Working Papers No. 3.186
    • Coretto, P.1    Hennig, C.2
  • 6
    • 0002231562 scopus 로고
    • The notion of breakdown point
    • P. J. Bickel, K. Doksum, and J. L. Hodges jr. (Eds.): Wadsworth, Belmont, CA
    • DONOHO, D. L. and HUBER, P. J. (1983): The notion of breakdown point. In P. J. Bickel, K. Doksum, and J. L. Hodges jr. (Eds.): A Festschrift for Erich L. Lehmann, Wadsworth, Belmont, CA, 157-184.
    • (1983) A Festschrift for Erich L. Lehmann , pp. 157-184
    • Donoho, D.L.1    Huber, P.J.2
  • 7
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters? Which clustering method? Answers via model based cluster analysis
    • FRALEY, C. and RAFTERY, A. E. (1998): How Many Clusters? Which Clustering Method? Answers Via Model Based Cluster Analysis. Computer Journal, 41, 578-588.
    • (1998) Computer Journal , vol.41 , pp. 578-588
    • Fraley, C.1    Raftery, A.E.2
  • 8
    • 0001354471 scopus 로고
    • A constrained formulation of maximum-likelihood estimates for normal mixture distributions
    • HATHAWAY, R. J. (1985): A constrained formulation of maximum-likelihood estimates for normal mixture distributions. Annals of Statistics, 13, 795-800.
    • (1985) Annals of Statistics , vol.13 , pp. 795-800
    • Hathaway, R.J.1
  • 9
    • 24344501318 scopus 로고    scopus 로고
    • Breakdown points for maximum likelihood-estimators of location-scale mixtures
    • HENNIG, C. (2004): Breakdown points for maximum likelihood-estimators of location-scale mixtures. Annals of Statistics, 32, 1313-1340.
    • (2004) Annals of Statistics , vol.32 , pp. 1313-1340
    • Hennig, C.1
  • 11
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and the em algorithm
    • REDNER, R. A. andWALKER, H. F. (1984): Mixture densities, maximum likelihood and the EM algorithm, SIAM Review, 26, 195-239.
    • (1984) SIAM Review , vol.26 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2
  • 12
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • SCHWARZ, G. (1978): Estimating the dimension of a model, Annals of Statistics, 6, 461-464.
    • (1978) Annals of Statistics , vol.6 , pp. 461-464
    • Schwarz, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.