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Volumn 4, Issue 1, 2010, Pages 3-34

Methods for merging Gaussian mixture components

Author keywords

Dip test; Model based cluster analysis; Multilayer mixture; Prediction strength; Ridgeline; Unimodality

Indexed keywords

ARRAY PROCESSING; CLUSTER ANALYSIS; FORECASTING; GAUSSIAN DISTRIBUTION; MERGING; MULTILAYERS; VISUALIZATION;

EID: 77955091542     PISSN: 18625347     EISSN: 18625355     Source Type: Journal    
DOI: 10.1007/s11634-010-0058-3     Document Type: Article
Times cited : (200)

References (26)
  • 1
    • 0027453616 scopus 로고
    • Model-based Gaussian and non-Gaussian clustering
    • Banfield JD, Raftery AE (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
  • 3
    • 0034228914 scopus 로고    scopus 로고
    • Assessing a mixture model for clustering with the integrated completed likelihood
    • Biernacki C, Celeux G, Govaert G (2000) Assessing a mixture model for clustering with the integrated completed likelihood. IEEE T Pattern Anal 22: 719-725.
    • (2000) IEEE T Pattern Anal , vol.22 , pp. 719-725
    • Biernacki, C.1    Celeux, G.2    Govaert, G.3
  • 4
    • 84970548695 scopus 로고
    • A multivariate study of variation in two species of rock crab of genus Leptograpsus
    • Campbell NA, Mahon RJ (1974) A multivariate study of variation in two species of rock crab of genus Leptograpsus. Aust J Zool 22: 417-425.
    • (1974) Aust J Zool , vol.22 , pp. 417-425
    • Campbell, N.A.1    Mahon, R.J.2
  • 5
    • 84983993025 scopus 로고
    • Data features
    • Davies PL (1995) Data features. Stat Neerl 49: 185-245.
    • (1995) Stat Neerl , vol.49 , pp. 185-245
    • Davies, P.L.1
  • 6
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering, discriminant analysis, and density estimation
    • Fraley C, Raftery AE (2002) Model-based clustering, discriminant analysis, and density estimation. J Am Stat Assoc 97: 611-631.
    • (2002) J Am Stat Assoc , vol.97 , pp. 611-631
    • Fraley, C.1    Raftery, A.E.2
  • 7
    • 0742306126 scopus 로고    scopus 로고
    • Enhanced software for model-based clustering, density estimation and discriminant analysis
    • Fraley C, Raftery AE (2003) Enhanced software for model-based clustering, density estimation and discriminant analysis. J Classif 20: 263-286.
    • (2003) J Classif , vol.20 , pp. 263-286
    • Fraley, C.1    Raftery, A.E.2
  • 9
    • 0002643986 scopus 로고
    • The dip test of unimodality
    • Hartigan JA, Hartigan PM (1985) The dip test of unimodality. Ann Stat 13: 70-84.
    • (1985) Ann Stat , vol.13 , pp. 70-84
    • Hartigan, J.A.1    Hartigan, P.M.2
  • 10
    • 0001131390 scopus 로고    scopus 로고
    • Discriminant analysis by Gaussian mixtures
    • Hastie T, Tibshirani R (1996) Discriminant analysis by Gaussian mixtures. J Roy Stat Soc B Met 58: 155-176.
    • (1996) J Roy Stat Soc B Met , vol.58 , pp. 155-176
    • Hastie, T.1    Tibshirani, R.2
  • 11
    • 11244342326 scopus 로고    scopus 로고
    • Asymmetric linear dimension reduction for classification
    • Hennig C (2005) Asymmetric linear dimension reduction for classification. J Comput Graph Stat 13: 930-945.
    • (2005) J Comput Graph Stat , vol.13 , pp. 930-945
    • Hennig, C.1
  • 12
    • 84858749722 scopus 로고    scopus 로고
    • Ridgeline plot and clusterwise stability as tools for merging Gaussian mixture components
    • H. Locarek-Junge and C. Weihs (Eds.), Berlin, accepted for publication: Springer
    • Hennig C (2010) Ridgeline plot and clusterwise stability as tools for merging Gaussian mixture components. In: Locarek-Junge H, Weihs C (eds) Classification as a tool for research. Springer, Berlin, accepted for publication.
    • (2010) Classification as a Tool for Research
    • Hennig, C.1
  • 13
    • 84879562466 scopus 로고    scopus 로고
    • The noise component in model-based cluster analysis
    • C. Preisach, H. Burkhard, L. Schmidt-Thieme, and R. Decker (Eds.), Berlin: Springer
    • Hennig C, Coretto P (2008) The noise component in model-based cluster analysis. In: Preisach C, Burkhard H, Schmidt-Thieme L, Decker R (eds) Data analysis, machine learning and applications. Springer, Berlin, pp 127-138.
    • (2008) Data Analysis, Machine Learning and Applications , pp. 127-138
    • Hennig, C.1    Coretto, P.2
  • 14
    • 0002954754 scopus 로고    scopus 로고
    • Consistent estimation of the order of a mixture model
    • Keribin C (2000) Consistent estimation of the order of a mixture model. Sankhya Ser A 62: 49-66.
    • (2000) Sankhya Ser A , vol.62 , pp. 49-66
    • Keribin, C.1
  • 15
    • 26644438098 scopus 로고    scopus 로고
    • Clustering based on a multilayer mixture model
    • Li J (2004) Clustering based on a multilayer mixture model. J Comput Graph Stat 14: 547-568.
    • (2004) J Comput Graph Stat , vol.14 , pp. 547-568
    • Li, J.1
  • 16
    • 51249188317 scopus 로고
    • Some properties of affinity and applications
    • Matusita K (1971) Some properties of affinity and applications. Ann I Stat Math 23: 137-155.
    • (1971) Ann I Stat Math , vol.23 , pp. 137-155
    • Matusita, K.1
  • 18
    • 33750744475 scopus 로고    scopus 로고
    • Generation of random clusters with specified degree of separation
    • Qiu W, Joe H (2006) Generation of random clusters with specified degree of separation. J Classif 23: 315-334.
    • (2006) J Classif , vol.23 , pp. 315-334
    • Qiu, W.1    Joe, H.2
  • 19
    • 30344468432 scopus 로고    scopus 로고
    • The topography of multivariate normal mixtures
    • Ray S, Lindsay BG (2005) The topography of multivariate normal mixtures. Ann Stat 33: 2042-2065.
    • (2005) Ann Stat , vol.33 , pp. 2042-2065
    • Ray, S.1    Lindsay, B.G.2
  • 20
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and the EM algorithm
    • Redner RA, Walker HF (1984) Mixture densities, maximum likelihood and the EM algorithm. SIAM Rev 26: 195-239.
    • (1984) SIAM Rev , vol.26 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2
  • 21
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6: 461-464.
    • (1978) Ann Stat , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 24
    • 26644472430 scopus 로고    scopus 로고
    • Cluster validation by prediction strength
    • Tibshirani R, Walther G (2005) Cluster validation by prediction strength. J Comput Graph Stat 14: 511-528.
    • (2005) J Comput Graph Stat , vol.14 , pp. 511-528
    • Tibshirani, R.1    Walther, G.2
  • 25
    • 0035532141 scopus 로고    scopus 로고
    • Estimating the number of clusters in a dataset via the gap statistic
    • Tibshirani R, Walther G, Hastie T (2001) Estimating the number of clusters in a dataset via the gap statistic. J Roy Stat Soc B Met 63: 411-423.
    • (2001) J Roy Stat Soc B Met , vol.63 , pp. 411-423
    • Tibshirani, R.1    Walther, G.2    Hastie, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.