Survey of Clustering Algorithms

Rui Xu; D. WunschII · IEEE Transactions on Neural Networks · 2005

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Rui Xu; D. WunschII

Publisher

IEEE Transactions on Neural Networks

Year

2005

Language

English

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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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APA 7

Xu, R. & WunschII, D. (2005). Survey of Clustering Algorithms. https://doi.org/10.1109/tnn.2005.845141

MLA

Xu, Rui, and D. WunschII. "Survey of Clustering Algorithms." 2005. https://doi.org/10.1109/tnn.2005.845141.

Chicago

Xu, Rui and D. WunschII. 2005. "Survey of Clustering Algorithms.". https://doi.org/10.1109/tnn.2005.845141.

Harvard

Xu, R. and WunschII, D. 2005, Survey of Clustering Algorithms, IEEE Transactions on Neural Networks, available at: https://doi.org/10.1109/tnn.2005.845141 [Accessed 7 Aug. 2026].

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Title: Survey of Clustering Algorithms

Author / contributors: Rui Xu; D. WunschII

Publisher: IEEE Transactions on Neural Networks

Publication year: 2005

Language: English

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Cluster analysis; Computer science; Travelling salesman problem; Confusion; Benchmark (surveying); Field (mathematics); Variety (cybernetics); Machine learning; Data mining; Data science; Artificial intelligence; Cluster (spacecraft)