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Volumn , Issue , 2009, Pages 790-792

K-means clustering algorithm with improved initial center

Author keywords

Data clustering; Initial center; K means

Indexed keywords

CLUSTERING ACCURACY; CLUSTERING METHODS; CLUSTERING NUMBER; DATA CLUSTERING; INITIAL CENTER; INITIAL VALUES; K-MEANS; K-MEANS ALGORITHM; K-MEANS CLUSTERING ALGORITHM; NUMBER OF CLUSTERS; SYNTHETIC DATASETS;

EID: 66249134301     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WKDD.2009.210     Document Type: Conference Paper
Times cited : (86)

References (9)
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    • Steinhaus, H.1
  • 2
    • 0020102027 scopus 로고
    • Last square quantization in PCM's
    • Bell Telephone Laboratories Paper (1957) Published in journal much later: S. P. Lloyd. Least squares quantization in PCM. Special issue on quantization
    • S. Lloyd, Last square quantization in PCM's. Bell Telephone Laboratories Paper (1957). Published in journal much later: S. P. Lloyd. Least squares quantization in PCM. Special issue on quantization, IEEE Trans. Inform. Theory, 28:129-137, 1982.
    • (1982) IEEE Trans. Inform. Theory , vol.28 , pp. 129-137
    • Lloyd, S.1
  • 6
    • 19044364181 scopus 로고    scopus 로고
    • Optimising kmeans clustering results with standard software packages
    • HAND, D.J., and KRZANOWSKI, W.J. (2005), "Optimising kmeans Clustering Results with Standard Software Packages", Computational Statisticsand DataAnalysis, 49, 969-973.
    • (2005) Computational Statisticsand DataAnalysis , vol.49 , pp. 969-973
    • Hand, D.J.1    Krzanowski, W.J.2
  • 7
    • 33744762091 scopus 로고    scopus 로고
    • Analysis of global K-means, An incremental heuristic for minimum sum-of-squares clustering
    • HANSEN,P.,NGAI,E.,CHEUNG,B.K.,and MLADENOVIC,N.(2005),"Analysis of GlobalK-means, An Incremental Heuristic for Minimum Sum-of-squares Clustering", Journal of Classification, 22, 287-310.
    • (2005) Journal of Classification , vol.22 , pp. 287-310
    • Hansen, P.1    Ngai, E.2    Cheung, B.K.3    Mladenovic, N.4
  • 9
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    • Neighborhood density method for selecting initial cluster centers in K-mean clustering
    • Yunming Ye.Neighborhood Density Method for Selecting Initial Cluster Centers in K-Mean Clustering In: Proceedings of PAKDD'06. (2006) pp. 189-198.
    • (2006) Proceedings of PAKDD'06. , pp. 189-198
    • Ye, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.