高维数据聚类方法综述
고유수거취류방법종술
Survey of clustering algorithms for high-dimensional data
  • 万方数据
    计算机应用研究 계산궤응용연구
    APPLICATION RESEARCH OF COMPUTERS
    2010年 1期 23-26,31 ,共5页

    贺玲%蔡益朝%杨征

    하령%채익조%양정

    高维数据%聚类%子空间 高維數據%聚類%子空間
    고유수거%취류%자공간
    high-dimensional data%clustering%subspace
    总结了高维数据聚类算法的研究现状,分析比较了算法性能的主要差异,并指出其今后的发展趋势,即在子空间聚类过程中融入其他传统聚类方法的思想,以提高聚类性能.
    총결료고유수거취류산법적연구현상,분석비교료산법성능적주요차이,병지출기금후적발전추세,즉재자공간취류과정중융입기타전통취류방법적사상,이제고취류성능.
    This paper provided a survey of current clustering algorithms for high-dimensional data at first, then made a comparison among them and identifized the new direction in the future, which was the combination of subspace clustering and other typical clustering methods.
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