Abstract
In this paper, the concept of a granulation order is proposed in an information system. The positive approximation of a set under a granulation order is defined. Some properties of positive approximation are obtained. For a set of the universe in an information system, its approximation accuracy is monotonously increasing under a granulation order. This means that a proper family of granulations can be chosen for a target concept approximation according to the user requirements. An algorithm based on positive approximation is designed for decision rule mining, and its application is illustrated by an example.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zadeh, L.A.: Fuzzy Sets and Information Granularity. In: Gupta, M., Ragade, R., Yager, R. (eds.) Advances in Fuzzy Set Theory and Application, pp. 3–18. North-Holland, Amsterdam (1979)
Zadeh, L.A.: Fuzzy logic=computing with words. IEEE Transactions on Fuzzy Systems 4(1), 103–111 (1996)
Zadeh, L.A.: Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems 90, 111–127 (1997)
Zadeh, L.A.: Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information intelligent systems. Soft Computing 2(1), 23–25 (1998)
Pawlak, Z.: Granularity of knowledge, indiscernibility and rough sets. In: Proceedings of 1998 IEEE International Conference on Fuzzy Systems, pp. 106–110 (1998)
Yao, Y.Y.: Granular computing: basic issues and possible solutions. In: Proceedings of the Fifth International Conference on Computing and Information, vol. I, pp. 186–189 (2000)
Lin, T.Y.: Granular computing on binary relations I: Data mining and neighborhood systems, II: Rough sets representations and belief functions. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery, vol. 1, pp. 107–140. Physica, Heidelberg (1998)
Zhang, L., Zhang, B.: Theory of fuzzy quotient space (methods of fuzzy granular computing). Journal of Software (in Chinese) 14(4), 770–776 (2003)
Klir, G.J.: Basic issues of computing with granular computing. In: Proceedings of 1998 IEEE International Conference on Fuzzy Systems, pp. 101–105 (1998)
Liang, J.Y., Shi, Z.Z.: The information entropy, rough entropy and knowledge granulation in rough set theory. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12(1), 37–46 (2004)
Liang, J.Y., Shi, Z.Z., Li, D.Y.: The information entropy, rough entropy and knowledge granulation in incomplete information systems. International Journal of General Systems (to appear)
Liu, Q.: Granules and applications of granular computing in logical reasoning. Journal of Computer Research and Development (in Chinese) 41(4), 546–551 (2004)
Zhang, W.X., Wu, W.Z., Liang, J.Y., Li, D.Y.: Theory and method of rough sets (in Chinese). Science Press, Beijing (2001)
Pawlak, Z.: Rough sets. Theoretical aspects of reasoning about data. Kluwer Academic Publishers, Dordrecht (1991)
Bazan, J., Nguyen, H.S., Skowron, A.: Rough set methods in approximation of hierarchical concepts. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 342–351. Springer, Heidelberg (2004)
Bazan, J., Nguyen, H.S., Skowron, A., Szczuka, M.: A view on rough set concept approximations. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds.) RSFDGrC 2003. LNCS (LNAI), vol. 2639, pp. 181–188. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liang, J., Qian, Y., Chu, C., Li, D., Wang, J. (2005). Rough Set Approximation Based on Dynamic Granulation. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548669_72
Download citation
DOI: https://doi.org/10.1007/11548669_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28653-0
Online ISBN: 978-3-540-31825-5
eBook Packages: Computer ScienceComputer Science (R0)