메뉴 건너뛰기




Volumn 3, Issue , 2005, Pages 2372-2379

Improvements to the scalability of multiobjective clustering

Author keywords

[No Author keywords available]

Indexed keywords

MULTIOBJECTIVE CLUSTERING; MUTATION; SCALABILITY;

EID: 27144451817     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (73)

References (14)
  • 2
    • 0005871804 scopus 로고    scopus 로고
    • PESA-II: Region-based selection in evolutionary multiobjective optimization
    • San Francisco, California. Morgan Kaufmann Publishers
    • David W. Corne, Nick R. Jerram, Joshua D. Knowles, and Martin J. Oates. PESA-II: Region-based selection in evolutionary multiobjective optimization. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 283-290, San Francisco, California, 2001. Morgan Kaufmann Publishers.
    • (2001) Proceedings of the Genetic and Evolutionary Computation Conference , pp. 283-290
    • Corne, D.W.1    Jerram, N.R.2    Knowles, J.D.3    Oates, M.J.4
  • 5
    • 24344488919 scopus 로고    scopus 로고
    • Multiobjective clustering with automatic determination of the number of clusters
    • UMIST, Manchester, UK
    • J. Handl and J. Knowles. Multiobjective clustering with automatic determination of the number of clusters. Technical Report TR-COMPSYSBIO-2004-02, UMIST, Manchester, UK, 2004.
    • (2004) Technical Report , vol.TR-COMPSYSBIO-2004-02
    • Handl, J.1    Knowles, J.2
  • 10
    • 0033204902 scopus 로고    scopus 로고
    • An empirical comparison of four initialization methods for the k-means algorithm
    • J. M. Pena, J, A. Lozana, and P. Larranaga. An empirical comparison of four initialization methods for the k-means algorithm. Pattern Recognition Letters, 20:1027-1040, 1999.
    • (1999) Pattern Recognition Letters , vol.20 , pp. 1027-1040
    • Pena, J.M.1    Lozana, J.A.2    Larranaga, P.3
  • 11
    • 0023453329 scopus 로고
    • Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
    • P. J. Rousseeuw. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20:53-65, 1987.
    • (1987) Journal of Computational and Applied Mathematics , vol.20 , pp. 53-65
    • Rousseeuw, P.J.1
  • 12
    • 0003998476 scopus 로고
    • Cubic clustering criterion
    • Cary, NC: SAS Institute Inc
    • W. S. Sarle. Cubic clustering criterion. Technical report, SAS Technical Report A-108, Cary, NC: SAS Institute Inc, 1983.
    • (1983) Technical Report, SAS Technical Report , vol.A-108
    • Sarle, W.S.1
  • 13
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles - A knowledge reuse framework for combining multiple partitions
    • A. Strehl and J. Ghosh. Cluster ensembles - a knowledge reuse framework for combining multiple partitions. Journal on Machine Learning Research, 3:583-617, 2002.
    • (2002) Journal on Machine Learning Research , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 14
    • 0003414440 scopus 로고    scopus 로고
    • Estimating the number of clusters in a dataset via the Gap statistic
    • Stanford University
    • R. Tibshirani, G. Walther, and T. Hastie. Estimating the number of clusters in a dataset via the Gap statistic. Technical report, Stanford University, 2000.
    • (2000) Technical Report
    • Tibshirani, R.1    Walther, G.2    Hastie, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.