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Clustering validity checking methods: part II
Abstract
Clustering results validation is an important topic in the context of pattern recognition. We review approaches and systems in this context. In the first part of this paper we presented clustering validity checking approaches based on internal and external criteria. In the second, current part, we present a review of clustering validity approaches based on relative criteria. Also we discuss the results of an experimental study based on widely known validity indices. Finally the paper illustrates the issues that are under-addressed by the recent approaches and proposes the research directions in the field.
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Cited by
A survey of techniques for internet traffic classification using machine learning
Nguyen, T. T. T., & Armitage, G. (2008) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2008.080406 · Cited by 1,664
Business intelligence: data mining and optimization for decision making
Vercellis, C., Ahmadi, A., & Mohebi, A. (2016) · doi:10.5281/zenodo.13983826 · Cited by 398
Relative clustering validity criteria: A comparative overview
Vendramin, L., Campello, R. J. G. B., & Hruschka, E. R. (2010) · Statistical Analysis and Data Mining: The ASA Data Science Journal · doi:10.1002/sam.10080 · Cited by 325
Valls, A., Gibert, K., Orellana, A., & Antón-Clavé, S. (2018) · Information & Management · doi:10.1016/j.im.2017.05.002 · Cited by 50
Metadata
- Authors
- Halkidi, M., Batistakis, Y., & Vazirgiannis, M.
- Venue
- ACM SIGMOD Record
- Published
- 2002-09
- Volume
- 31
- Issue
- 3
- Pages
- 19-27
- ISSN
- 0163-5808 (ISSN-L)
- OpenAlex
- W2043793719
- Cited by
- 466
- References
- 0
- FWCI
- 4.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- Halkidi, M., Batistakis, Y., & Vazirgiannis, M. (2002). Clustering validity checking methods: part II. ACM SIGMOD Record. https://doi.org/10.1145/601858.601862
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