Abstract
In this paper, element equivalence class with dynamic characteristic is introduced into Z.Pawlak rough sets, and it is extended to singular rough sets, singular rough sets has dynamic characteristics. By using of singular rough sets, this paper presents a method for updating approximations of a set, such method can support incremental updating of approximations, which is essential to dealing with dynamic attribute generalization, results in this paper can be applied to rough classification efficiently from very large data bases.
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References
Pawlak, Z.: Rough Sets. International Journal of Computer and Information Sciences 11, 341–356 (1982)
Shi, K.: S-rough sets and its applications in diagnosis-recognition for disease. In: IEEE proceedings of the First International Conference on Machine Learning and Cybernetics, vol. 1, pp. 50–54 (2002)
Shi, K., Cui, Y.: F-decomposition and \(\overline{F}\)-reduction of S-rough sets. An International Journal Advances in System Sciences and Applications 4, 487–499 (2004)
Shi, K., Cui, Y.: One direction S-rough decision and its decision model. In: IEEE Proceedings of the International Conference on Machine Leaning and Cybernetics, vol. 3, pp. 1073–1078 (2004)
shi, K.: S-rough Sets and Knowledge Separation. Journal of Systems Engineering and Electronics 2, 401–410 (2005)
Shi, K., Chang, T.: One direction S-rough sets. International Journal of Fuzzy Mathematics 2, 319–334 (2005)
Shi, K.: Two direction S-rough sets. International Journal of Fuzzy Mathematics 2, 335–349 (2005)
Hu, H., Wang, H., Shi, K.: Two direction S-Rough recognition of Knowledge and Recognition Model. International Advances in Systems Science and Application 3, 368–374 (2005)
Hu, H., Yin, S.: Knowledge rough recognition on assistant set of two direction S-rough sets and recognition model. In: IEEE Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, vol. 4, pp. 1910–1916 (2005)
Hu, H., Xue, P., Fu, H.: S-Rough Recognition of Knowledge and General Threshold Encryption Authentication Scheme of Recognition Conclusion. In: The 6th international conference on intelligent system design and applications, vol. 1, pp. 816–821 (2006)
Hu, H., Wang, Y., Shi, K.: S-rough communication and its characteristics. Journal of System Engineering and Electronics 1, 148–154 (2007)
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© 2009 Springer-Verlag Berlin Heidelberg
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Hu, Hq., Fu, Hy., Shi, Kq. (2009). Singular Rough Sets Method in Attribute Generalization. In: Cao, By., Zhang, Cy., Li, Tf. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88914-4_78
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DOI: https://doi.org/10.1007/978-3-540-88914-4_78
Publisher Name: Springer, Berlin, Heidelberg
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