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Volumn , Issue , 2010, Pages

An extension of global fuzzy c-means using kernel methods

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING METHODS; CONVEX CLUSTERS; FUZZY C MEAN; FUZZY C-MEANS; KERNEL METHODS; NON-LINEAR; REAL WORLD DATA; SEED SELECTION;

EID: 78549250692     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2010.5584271     Document Type: Conference Paper
Times cited : (9)

References (17)
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    • The global k-means clustering algorithm
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  • 9
    • 45549104169 scopus 로고    scopus 로고
    • Modified global k-means algorithm for minimum sum-of-squares clustering problems
    • A. M. Bagirov, "Modified global k-means algorithm for minimum sum-of-squares clustering problems," Pattern Recognition, vol. 41, pp.3192-3199, 2008.
    • (2008) Pattern Recognition , vol.41 , pp. 3192-3199
    • Bagirov, A.M.1
  • 13
    • 57849144858 scopus 로고
    • Optimization of clustering criteria by reformulation
    • R. J. Hathaway and J. C. Bezdek, "Optimization of clustering criteria by reformulation," IEEE Transactions on Fuzzy Systems, vol. 3, no. 2,pp. 241-245, 1995.
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    • Hathaway, R.J.1    Bezdek, J.C.2
  • 14
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    • Mercer kernel-based clustering in feature space
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    • Girolami, M.1
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    • 34548025132 scopus 로고    scopus 로고
    • A survey of kernel and spectral methods for clustering
    • M. Filippone, F. Camastra, F. Masulli, and S. Rovetta, "A survey of kernel and spectral methods for clustering," Pattern Recognition, vol. 41, no. 1, pp. 176-190, 2008.
    • (2008) Pattern Recognition , vol.41 , Issue.1 , pp. 176-190
    • Filippone, M.1    Camastra, F.2    Masulli, F.3    Rovetta, S.4
  • 16
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    • Meila, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.