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Volumn 5259 LNCS, Issue , 2008, Pages 664-673

Knee point detection in BIC for detecting the number of clusters

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION;

EID: 57049189677     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88458-3_60     Document Type: Conference Paper
Times cited : (99)

References (14)
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    • An examination of procedures for determining the number of clusters in a data set
    • Milligan, G.W., Cooper, M.C.: An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159-179 (1985)
    • (1985) Psychometrika , vol.50 , pp. 159-179
    • Milligan, G.W.1    Cooper, M.C.2
  • 2
    • 0036011451 scopus 로고    scopus 로고
    • An examination of indexes for determining the number of clusters in binary data sets
    • Dimitriadou, E., Dolnicar, S., Weingassel, A.: An examination of indexes for determining the number of clusters in binary data sets. Psychometrika 67(1), 137-160 (2002)
    • (2002) Psychometrika , vol.67 , Issue.1 , pp. 137-160
    • Dimitriadou, E.1    Dolnicar, S.2    Weingassel, A.3
  • 3
    • 84972893020 scopus 로고    scopus 로고
    • Calinski, T., Harabasz, J.: A dendrite method for cluster analysis. Communication in statistics 3,1.-27 (1974)
    • Calinski, T., Harabasz, J.: A dendrite method for cluster analysis. Communication in statistics 3,1.-27 (1974)
  • 4
    • 84941155240 scopus 로고
    • Well separated clusters and optimal fuzzy partitions
    • Dunn, J.C.: Well separated clusters and optimal fuzzy partitions. Journal of Cybernetica 4, 95-104 (1974)
    • (1974) Journal of Cybernetica , vol.4 , pp. 95-104
    • Dunn, J.C.1
  • 7
    • 85143001779 scopus 로고    scopus 로고
    • Xie, X.L., Beni, G.: A validity measure for fuzzy clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence 1.3(8), 841-847 (199.1)
    • Xie, X.L., Beni, G.: A validity measure for fuzzy clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence 1.3(8), 841-847 (199.1)
  • 9
    • 0003862207 scopus 로고    scopus 로고
    • How many clusters? Which clustering method? answers via model-based cluster analysis
    • Technical Report no. 329, Department of Statistics, University of Washington
    • Frayley, C., Raftery, A.: How many clusters? Which clustering method? answers via model-based cluster analysis. Technical Report no. 329, Department of Statistics, University of Washington (1998)
    • (1998)
    • Frayley, C.1    Raftery, A.2
  • 11
    • 0023905024 scopus 로고
    • A criterion for determining the number of groups in a data set using sum-of-squares clustering
    • Krzanowski, W.J., Lai, Y.T.: A criterion for determining the number of groups in a data set using sum-of-squares clustering. Biometrics 44(1), 23-34 (1988)
    • (1988) Biometrics , vol.44 , Issue.1 , pp. 23-34
    • Krzanowski, W.J.1    Lai, Y.T.2
  • 13
    • 27944462549 scopus 로고
    • A reference Bayesian test for nested Hypotheses and its relationship to the Schwarz Criterion
    • Kass, R.E., Wasserman, L.: A reference Bayesian test for nested Hypotheses and its relationship to the Schwarz Criterion. Journal of the American Statistical Association 90(431), 928-934 (1995)
    • (1995) Journal of the American Statistical Association , vol.90 , Issue.431 , pp. 928-934
    • Kass, R.E.1    Wasserman, L.2
  • 14
    • 0034345982 scopus 로고    scopus 로고
    • Randomized local search algorithm for the clustering problem
    • Fränti, P., Kivijärvi, J.: Randomized local search algorithm for the clustering problem. Pattern Analysis and Applications 3(4), 358-369 (2000)
    • (2000) Pattern Analysis and Applications , vol.3 , Issue.4 , pp. 358-369
    • Fränti, P.1    Kivijärvi, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.