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Advances in Soft Computing
Volumn 54, Issue , 2009, Pages 448-455
New modification of fuzzy c-means clustering algorithm
Author keywords

Euclidean distance; FCM algorithm; Friedman test; Mahalanobis distance
Indexed keywords

EID: 79952167270     PISSN: 16153871     EISSN: 18600794     Source Type: Book Series    
DOI: 10.1007/978-3-540-88914-4_55     Document Type: Conference Paper
Times cited : (7)
References (10)
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    • Dunn, J.C.1
  • 3
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    • Alternative c-means clustering algorithms
    • Wu, K. L., Yang, M. S.: Alternative c-means clustering algorithms. Pattern Recognition 120, 249-254 (2001)
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    • Wu, K.L.1    Yang, M.S.2
  • 4
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    • New modifications and applications of fuzzy c-means methodology
    • doi:10.1016/j.csda.2007.10.020
    • Berget, I., Mevik, B. H., Nas, T.: New modifications and applications of fuzzy c-means methodology. Computational Statistics & Data Analysis (2007) doi:10.1016/j.csda.2007.10.020
    • (2007) Computational Statistics & Data Analysis
    • Berget, I.1    Mevik, B.H.2    Nas, T.3
  • 5
    • 2942534051 scopus 로고    scopus 로고
    • Improving fuzzy c-means clustering based on feature-weight learning
    • DOI 10.1016/j.patrec.2004.03.008, PII S0167865504000765
    • Wang, X. Z., Wang, Y. D., Wang, L.: Improving fuzzy c-means clustering based on feature-weighted learning. Pattern Recognition Letters 25, 1123-1132 (2004) (Pubitemid 38763654)
    • (2004) Pattern Recognition Letters , vol.25 , Issue.10 , pp. 1123-1132
    • Wang, X.1    Wang, Y.2    Wang, L.3
  • 6
    • 0003064389 scopus 로고    scopus 로고
    • Membership functions in the fuzzy C-means algorithm
    • PII S0165011497000626
    • Sintas, A. F., Cadenas, J. M., Martin, F.: Membership functions in the fuzzy c-means algorithm. Fuzzy Sets and Systems 101, 49-58 (1999) (Pubitemid 129662646)
    • (1999) Fuzzy Sets and Systems , vol.101 , Issue.1 , pp. 49-58
    • Flores-Sintas, A.1    Cadenas, J.M.2    Martin, F.3
  • 7
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    • Optimal number of clusters and the best partion in fuzzy c-means
    • Chinese
    • Zhu, K. J., Shu, S. H., Li, J. L.: Optimal number of clusters and the best partion in fuzzy c-means. Systems, Engineering-Theory and Practice 3, 52-61 (2005) (in Chinese)
    • (2005) Systems, Engineering-theory and Practice , vol.3 , pp. 52-61
    • Zhu, K.J.1    Shu, S.H.2    Li, J.L.3
  • 9
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    • The use of multiple measurements in taxonomic problems
    • Fisher, R.: The use of multiple measurements in taxonomic problems. Ann. Eugenics 7, 179-188 (1936)
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  • 10
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    • Bootstrapping approach to feature-weight selection in fuzzy c-means algorithms with an application in color image segmentation
    • doi:10.1016/j.patrec.2008.02.003
    • Hung, W. L., Yang, M. S., Chen, D. H.: Bootstrapping approach to feature-weight selection in fuzzy c-means algorithms with an application in color image segmentation. Pattern Recognition Letters (2008) doi:10.1016/j.patrec.2008.02.003
    • (2008) Pattern Recognition Letters
    • Hung, W.L.1    Yang, M.S.2    Chen, D.H.3

* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.