Survey of clustering algorithms
R. Xu, und I. Wunsch.
Neural Networks, IEEE Transactions on 16 (3): 645--678 (2005)

Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity, on one hand, equips us with many tools. On the other hand, the profusion of options causes confusion. We survey clustering algorithms for data sets appearing in statistics, computer science, and machine learning, and illustrate their applications in some benchmark data sets, the traveling salesman problem, and bioinformatics, a new field attracting intensive efforts. Several tightly related topics, proximity measure, and cluster validation, are also discussed.

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@article{Rui05SurveyClustering,
  abstract = {Data analysis plays an indispensable role for understanding various
	phenomena. Cluster analysis, primitive exploration with little or
	no prior knowledge, consists of research developed across a wide
	variety of communities. The diversity, on one hand, equips us with
	many tools. On the other hand, the profusion of options causes confusion.
	We survey clustering algorithms for data sets appearing in statistics,
	computer science, and machine learning, and illustrate their applications
	in some benchmark data sets, the traveling salesman problem, and
	bioinformatics, a new field attracting intensive efforts. Several
	tightly related topics, proximity measure, and cluster validation,
	are also discussed.},
  added-at = {2007-03-18T13:33:04.000+0100},
  author = {Xu, Rui and Wunsch, II},
  biburl = {https://puma.uni-kassel.de/bibtex/292c03ba02a41f95ae315273939c8daa5/hotho},
  interhash = {7bd8c3f3c7ea707f110d76123e0d097c},
  intrahash = {92c03ba02a41f95ae315273939c8daa5},
  issn = {1045-9227},
  journal = {Neural Networks, IEEE Transactions on},
  keywords = {clustering survey toread},
  number = 3,
  owner = {mgrani},
  pages = {645--678},
  timestamp = {2007-03-18T13:33:04.000+0100},
  title = {Survey of clustering algorithms},
  volume = 16,
  year = 2005
}

%0 Journal Article
%1 Rui05SurveyClustering
%A Xu, Rui
%A Wunsch, II
%D 2005
%J Neural Networks, IEEE Transactions on
%K clustering survey toread
%N 3
%P 645--678
%T Survey of clustering algorithms
%V 16
%X Data analysis plays an indispensable role for understanding various
	phenomena. Cluster analysis, primitive exploration with little or
	no prior knowledge, consists of research developed across a wide
	variety of communities. The diversity, on one hand, equips us with
	many tools. On the other hand, the profusion of options causes confusion.
	We survey clustering algorithms for data sets appearing in statistics,
	computer science, and machine learning, and illustrate their applications
	in some benchmark data sets, the traveling salesman problem, and
	bioinformatics, a new field attracting intensive efforts. Several
	tightly related topics, proximity measure, and cluster validation,
	are also discussed.

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Survey of clustering algorithms
R. Xu, und I. Wunsch.
Neural Networks, IEEE Transactions on 16 (3): 645--678 (2005)

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Survey of clustering algorithmsR. Xu, und I. Wunsch. Neural Networks, IEEE Transactions on 16 (3): 645--678 (2005)

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Survey of clustering algorithms
R. Xu, und I. Wunsch.
Neural Networks, IEEE Transactions on 16 (3): 645--678 (2005)