A novel research on rough clustering algorithm
Journal article, Peer reviewed
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Original versionQu, T., Lu, J., Karimi, H. R., & Xu, E. (2014). A novel research on rough clustering algorithm. Abstract and Applied Analysis, 2014, 1-6. doi: 10.1155/2014/205062 10.1155/2014/205062
The aim of this study is focusing the issue of traditional clustering algorithm subjects to data space distribution influence, a novel clustering algortihm combined with rough set theory is employed to the normal clustering. The proposed rough clustering algorithm takes the condition attributes and decision attributes displayed in the information table as the consistency principle, meanwhile it takes the data supercubic and information entropy to realize data attribute shortcutting and discretizing. Based on above discussion, by applying assemble feature vector addition principle computiation only one scanning information table can realize clustering for the data subject. Experiments reveal that the proposed algorithm is efficient and feasible.
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/205062 Open Access