An overview of clustering methods

被引:254
作者
Omran, Mahamed G. H. [1 ]
Engelbrecht, Andries P. [2 ]
Salman, Ayed [3 ]
机构
[1] Gulf Univ Sci & Technol, Dept Comp Sci, Hawally, Kuwait
[2] Univ Pretoria, Sch Informat Technol, Dept Comp Sci, ZA-0002 Pretoria, South Africa
[3] Kuwait Univ, Dept Comp Engn, Safat 13060, Kuwait
关键词
clustering; clustering validation; hard clustering; fuzzy clustering; unsupervised learning;
D O I
10.3233/IDA-2007-11602
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data clustering is the process of identifying natural groupings or clusters within multidimensional data based on some similarity measure. Clustering is a fundamental process in many different disciplines. Hence, researchers from different fields are actively working on the clustering problem. This paper provides an overview of the different representative clustering methods. In addition, several clustering validations indices are shown. Furthermore, approaches to automatically determine the number of clusters are presented. Finally, application of different heuristic approaches to the clustering problem is also investigated.
引用
收藏
页码:583 / 605
页数:23
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