- Title
- Classes and clusters in data analysis
- Creator
- Rubinov, Alex; Sukhorukova, Nadezda; Ugon, Julien
- Date
- 2006
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/32593
- Identifier
- vital:764
- Identifier
-
https://doi.org/10.1016/j.ejor.2005.04.047
- Identifier
- ISSN:0377-2217
- Abstract
- We discuss the relation between classes and clusters in datasets with given classes. We examine the distribution of classes within obtained clusters, using different clustering methods which are based on different techniques. We also study the structure of the obtained clusters. One of the main conclusions, obtained in this research is that the notion purity cannot be always used for evaluation of accuracy of clustering techniques. (c) 2005 Elsevier B.V. All rights reserved.; C1
- Publisher
- Elsevier Science
- Relation
- European Journal of Operational Research Vol. 173, no. 3 (Sep 2006), p. 849-865
- Rights
- Copyright Elsevier B.V.
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0102 Applied Mathematics; Data mining; Dataset with classes; Point-based clustering; Optimisation clustering model; Comparison of classes and clusters
- Full Text
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