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Volumn 13, Issue 3-4, 1997, Pages 269-278

Clustering for binary data and mixture models - Choice of the model

Author keywords

Akaike criterion; Bernoulli mixtures; Cluster analysis; Entropy criterion; Mixture approach

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; EIGENVALUES AND EIGENFUNCTIONS; MATRIX ALGEBRA; MONTE CARLO METHODS; RANDOM PROCESSES;

EID: 0031223058     PISSN: 87550024     EISSN: None     Source Type: Journal    
DOI: 10.1002/(sici)1099-0747(199709/12)13:3/4<269::aid-asm321>3.0.co;2-7     Document Type: Article
Times cited : (14)

References (17)
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    • H. Bozdogan, 'Choosing the number of component clusters in the mixture model using a new informational complexity criterion of the inverse-Fisher information matrix', in O. Opitz, B. Lausen and R. Klar (eds), Information and Classification, Springer-Verlag, Heidelberg, Germany, 1993, pp. 40-54.
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    • to be published
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.