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Erschienen in:
2011 | OriginalPaper | Buchkapitel
A Soft Set Model on Information System and Its Application in Clustering Attribute Selection
verfasst von : Hongwu Qin, Xiuqin Ma, Jasni Mohamad Zain, Norrozila Sulaiman, Tutut Herawan
Erschienen in: Software Engineering and Computer Systems
Verlag: Springer Berlin Heidelberg
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In this paper, we define a soft set model on the set of equivalence classes in an information system, which can be easily applied to obtaining approximation sets of rough set. Furthermore, we use it to select clustering attribute for categorical data clustering and a heuristic algorithm is presented. Experiment results on UCI benchmark data sets show that the proposed approach provides faster decision for selecting a clustering attribute as compared with maximum dependency attributes (MDA) approach.