Abstract
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.
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References
Molodtsov, D.: Soft set theory_first results. Comput. Math. Appl. 37, 19–31 (1999)
Pawlak, Z.: Rough sets. International Journal Information Computer Science 11, 341–356 (1982)
Pawlak, Z., Skowron, A.: Rudiments of rough sets. Information Sciences: An International Journal 177(1), 3–27 (2007)
Feng, F., Li, C., Davvaz, B., Ali, M.I.: Soft sets combined with fuzzy sets and rough sets: a tentative approach. In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, pp. 899–911. Springer, Heidelberg (2009)
Herawan, T., Deris, M.M.: A direct proof of every rough set is a soft set. In: Proceeding of the Third Asia International Conference on Modeling and Simulation, pp. 119–124 (2009)
UCI Repository of Machine Learning Databases, http://www.ics.uci.edu/~mlearn/MLRRepository.html
Mazlack, L.J., He, A., Zhu, Y., Coppock, S.: A rough set approach in choosing clustering attributes. In: Proceedings of the ISCA 13th International Conference (CAINE 2000), pp. 1–6 (2000)
Parmar, D., Wu, T., Blackhurst, J.: MMR: an algorithm for clustering categorical data using rough set theory. Data and Knowledge Engineering 63, 879–893 (2007)
Yao, Y.Y.: Information granulation and rough set approximation. International Journal of Intelligent Systems 16(1), 87–104 (2001)
Herawan, T., Deris, M.M., Abawajy, J.H.: A rough set approach for selecting clustering attribute. Knowledge-Based Systems 23, 220–231 (2010)
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© 2011 Springer-Verlag Berlin Heidelberg
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Qin, H., Ma, X., Mohamad Zain, J., Sulaiman, N., Herawan, T. (2011). A Soft Set Model on Information System and Its Application in Clustering Attribute Selection. In: Zain, J.M., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22191-0_2
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DOI: https://doi.org/10.1007/978-3-642-22191-0_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22190-3
Online ISBN: 978-3-642-22191-0
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