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Autonomous clustering using rough set theory
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Bean, Charlotte and Kambhampati, Chandra (2008) Autonomous clustering using rough set theory. International Journal of Automation and Computing , Vol.5 (No.1). pp. 90-102. doi:10.1007/s11633-008-0090-3 ISSN 1476-8186.
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Official URL: http://dx.doi.org/10.1007/s11633-008-0090-3
Abstract
This paper proposes a clustering technique that minimises the need for subjective
human intervention and is based on elements of rough set theory. The proposed algorithm is
unified in its approach to clustering and makes use of both local and global data properties to
obtain clustering solutions. It handles single-type and mixed attribute data sets with ease and
results from three data sets of single and mixed attribute types are used to illustrate the
technique and establish its efficiency.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School | ||||
Library of Congress Subject Headings (LCSH): | Rough sets, Cluster analysis | ||||
Journal or Publication Title: | International Journal of Automation and Computing | ||||
Publisher: | Springer Verlag | ||||
ISSN: | 1476-8186 | ||||
Official Date: | January 2008 | ||||
Dates: |
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Volume: | Vol.5 | ||||
Number: | No.1 | ||||
Page Range: | pp. 90-102 | ||||
DOI: | 10.1007/s11633-008-0090-3 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
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