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Volumn 62, Issue 5, 2011, Pages 2200-2208

Sample-weighted clustering methods

Author keywords

Cluster analysis; Fuzzy c means; k means; Maximum entropy principle; Robustness; Sample weights

Indexed keywords

CLUSTERING METHODS; CONVERGENCE PROPERTIES; DATA SETS; FUZZY C MEAN; FUZZY C-MEANS; K-MEANS; MAXIMUM ENTROPY PRINCIPLE; NUMERICAL DATA; REAL DATA SETS; ROBUST CLUSTERING; SAMPLE WEIGHTS;

EID: 80052263784     PISSN: 08981221     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.camwa.2011.07.005     Document Type: Article
Times cited : (22)

References (34)
  • 3
    • 0001457509 scopus 로고
    • Some methods for classification and analysis of multivariate observations
    • J. MacQueen, Some methods for classification and analysis of multivariate observations, in: Proc. 5th Berkeley Symp. Math. Statist, Prob. 1, 1967, pp. 281297.
    • (1967) Proc. 5th Berkeley Symp. Math. Statist, Prob. , vol.1 , pp. 281-297
    • MacQueen, J.1
  • 8
    • 34347231626 scopus 로고    scopus 로고
    • Mean shift-based clustering
    • K.L. Wu, and M.S. Yang Mean shift-based clustering Pattern Recognition 40 2007 3035 3052
    • (2007) Pattern Recognition , vol.40 , pp. 3035-3052
    • Wu, K.L.1    Yang, M.S.2
  • 10
    • 79551622290 scopus 로고    scopus 로고
    • A robust automatic merging possibilistic clustering method
    • M.S. Yang, and C.Y. Lai A robust automatic merging possibilistic clustering method IEEE Transactions on Fuzzy Systems 19 2011 26 41
    • (2011) IEEE Transactions on Fuzzy Systems , vol.19 , pp. 26-41
    • Yang, M.S.1    Lai, C.Y.2
  • 11
    • 0042312608 scopus 로고    scopus 로고
    • Feature weighting in k-means clustering
    • D.S. Modha, and W.S. Spangler Feature weighting in k-means clustering Machine Learning 52 2003 217 237
    • (2003) Machine Learning , vol.52 , pp. 217-237
    • Modha, D.S.1    Spangler, W.S.2
  • 13
    • 2942534051 scopus 로고    scopus 로고
    • Improving fuzzy c-means clustering based on feature-weight learning
    • X.Z. Wang, Y.D. Wang, and L.J. Wang Improving fuzzy c-means clustering based on feature-weight learning Pattern Recognition Letters 25 2004 1123 1132
    • (2004) Pattern Recognition Letters , vol.25 , pp. 1123-1132
    • Wang, X.Z.1    Wang, Y.D.2    Wang, L.J.3
  • 14
    • 43249103345 scopus 로고    scopus 로고
    • Bootstrapping approach to feature-weight selection in fuzzy c-means algorithms with an application in color image segmentation
    • W.L. Hung, M.S. Yang, and D.H. Chen Bootstrapping approach to feature-weight selection in fuzzy c-means algorithms with an application in color image segmentation Pattern Recognition Letters 29 2008 1317 1325
    • (2008) Pattern Recognition Letters , vol.29 , pp. 1317-1325
    • Hung, W.L.1    Yang, M.S.2    Chen, D.H.3
  • 15
    • 0037403098 scopus 로고    scopus 로고
    • Feature selection based on a modified fuzzy c-means algorithm with supervision
    • F. Marcelloni Feature selection based on a modified fuzzy c-means algorithm with supervision Information Sciences 151 2003 201 226
    • (2003) Information Sciences , vol.151 , pp. 201-226
    • Marcelloni, F.1
  • 17
    • 78650291481 scopus 로고    scopus 로고
    • A unifying criterion for unsupervised clustering and feature selection
    • M. Breaban, and H. Luchian A unifying criterion for unsupervised clustering and feature selection Pattern Recognition 44 2011 854 865
    • (2011) Pattern Recognition , vol.44 , pp. 854-865
    • Breaban, M.1    Luchian, H.2
  • 19
    • 0032202775 scopus 로고    scopus 로고
    • Deterministic annealing for clustering, compression, classification, regression, and related optimization problems
    • PII S0018921998078608
    • K. Rose Deterministic annealing for clustering, compression, classification, regression, and related optimization problems Proceedings of the IEEE 86 1998 2210 2239 (Pubitemid 128720301)
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2210-2239
    • Rose, K.1
  • 25
    • 0031211090 scopus 로고    scopus 로고
    • A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
    • Y. Freund, and R.E. Schapire A decision-theoretic generalization of online learning and an application to boosting Journal of Computer and System Sciences 55 1997 119 139 (Pubitemid 127433398)
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 27
    • 0000963889 scopus 로고
    • Strong consistency of k-means clustering
    • D. Pollard Strong consistency of k-means clustering Annals of Statistics 9 1981 135 140
    • (1981) Annals of Statistics , vol.9 , pp. 135-140
    • Pollard, D.1
  • 28
  • 30
    • 0028543130 scopus 로고
    • Optimality tests for the fuzzy c-means algorithm
    • DOI 10.1016/0031-3203(94)90134-1
    • W. Wei, and J.M. Mendel Optimality tests for the fuzzy c-means algorithms Pattern Recognition 27 1994 1567 1573 (Pubitemid 124017645)
    • (1994) Pattern Recognition , vol.27 , Issue.11 , pp. 1567-1573
    • Wei, W.1    Mendel, J.M.2
  • 31
    • 14644432442 scopus 로고    scopus 로고
    • Optimality test for generalized FCM and its application to parameter selection
    • DOI 10.1109/TFUZZ.2004.836065
    • J. Yu, and M.S. Yang Optimality test for generalized FCM and its application to parameter selection IEEE Transactions on Fuzzy Systems 13 2005 164 176 (Pubitemid 40319317)
    • (2005) IEEE Transactions on Fuzzy Systems , vol.13 , Issue.1 , pp. 164-176
    • Yu, J.1    Yang, M.-S.2
  • 32
    • 0002210265 scopus 로고
    • On the convergence properties of the em algorithm
    • C.F.J. Wu On the convergence properties of the EM algorithm Annals of Statistics 11 1983 95 103
    • (1983) Annals of Statistics , vol.11 , pp. 95-103
    • Wu, C.F.J.1
  • 33
    • 2342533082 scopus 로고    scopus 로고
    • On the convergence properties of the EM algorithm for Gaussian mixtures
    • L. Xu, and M.I. Jordan On the convergence properties of the EM algorithm for Gaussian mixtures Neural Computation 8 1996 129 151 (Pubitemid 126449919)
    • (1996) Neural Computation , vol.8 , Issue.1 , pp. 129-151
    • Xu, L.1    Jordan, M.I.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.