The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Survey of Clustering Algorithms
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.
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Cites
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Cited by
Clustering by fast search and find of density peaks
Rodriguez, A., & Laio, A. (2014) · Science · doi:10.1126/science.1242072 · Cited by 4,942
A Comprehensive Survey of Clustering Algorithms
Xu, D., & Tian, Y. (2015) · Annals of Data Science · doi:10.1007/s40745-015-0040-1 · Cited by 1,939
Classification in the Presence of Label Noise: A Survey
Frenay, B., & Verleysen, M. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2013.2292894 · Cited by 1,777
A survey of techniques for internet traffic classification using machine learning
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Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection
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Metadata
- Authors
- Xu, R., & WunschII, D.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 2005-05
- Volume
- 16
- Issue
- 3
- Pages
- 645-678
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2153233077
- Cited by
- 6,197
- References
- 17
- FWCI
- 128.83
- Type
- journal article
- Language
- en
- Open access
- closed
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