- Title
- Optimization approach for clustering datasets with weights
- Creator
- Ghosh, Ranadhir; Rubinov, Alex; Zhang, Jiapu
- Date
- 2005
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/38538
- Identifier
- vital:328
- Identifier
-
https://doi.org/10.1080/10556780512331318191
- Identifier
- ISSN:1055-6788
- Abstract
- We introduce datasets with weights and suggest using the minimization of some highly nonsmooth functions for clustering of such datasets. Datasets with weights often appear as the result of an approximation of large-scale datasets. We examine such approximations and also consider the application of datasets with weights to examine self-organizing maps. Results of some numerical experiments are presented and discussed.; C1
- Publisher
- Taylor & Francis
- Relation
- Optimization Methods & Software Vol. 20, no. 2-3 (Apr-Jun 2005), p. 329-345
- Rights
- Copyright Taylor and Francis
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0103 Numerical and Computational Mathematics; Datasets with weights; Nonsmooth optimization; Cluster function; Bradley-mangasarian approximation; Computer science; Software engineering; Operations research & management science; Applied mathematics
- Full Text
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