Abstract
To reduce the time complexity of attribute reduction algorithm based on discernibility matrix, a simplified decision table is first introduced, and an algorithm with time complexity (| O C||U|) is designed for calculating the simplified decision table. And then, a new measure of the significance of an attribute is defined for reducing the search space of simplified decision table. A recursive algorithm is proposed for computing the attribute significance that its time complexity is of O(|U/C|). Finally, an efficient attribute reduction algorithm is developed based on the attribute significance. This algorithm is equal to existing algorithms in performance and its time complexity is O(|C||U|) +O(|C|2|U/C|)
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Pawlak, Z.: Rough set theory and its application to data analysis. Cybernetics and Systems 9, 661–668 (1998)
Guan, J.W., Bell, D.A.: Rough computational methods for information systems. Artificial intelligence 105, 77–103 (1998)
Nguyen, S.H., Nguyen, H.S.: Some efficient algorithms for rough set methods. In: Proceedings of the Conference of Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU’96, Granada, Spain, pp. 1451–1456 (1996)
Skowron, A., Rauszer, C.: The discernibilinity matrices and functions in information systems. In: Slowincki, R. (ed.) Intelligent decision support-handbook of applications and advances of the rough sets theory, pp. 331–362. Kluwer Academic Publishers, Dordrecht (1992)
Hu, X.H., Cercone, N.: Learning in relational databases: A rough set approach. International journal of computational intelligence 11, 323–338 (1995)
Kkryszkiewicz, M.: Comparative study of alternative types of knowledge reduction in inconsistent systems. International Journal of Intelligent Systems 16, 105–120 (2001)
Li, D.R., Zhang, B.: On knowledge reduction inconsistent decision information systems. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems 50, 651–672 (2004)
Wang, J., Cui, J., Zhao, C.: Investigation on AQ11, ID3 and the Principle of Discernibility Matrix. Journal of Computer Science and Technology 16, 1–12 (2001)
Wang, J., Wang, J.: Reduction algorithms based on discernibility matrix: the ordered attributes method. Journal of Computer Science and Technology 16, 489–504 (2001)
Zhang, J., Wang, J., Li, D., He, H., Sun, J.: A new heuristic reduct algorithm base on rough sets theory. In: Dong, G., Tang, C.-j., Wang, W. (eds.) WAIM 2003. LNCS, vol. 2762, pp. 247–253. Springer, Heidelberg (2003)
Wang, B., Chen, S.B.: A complete algorithm for attribute reduction. In: Tarn, T.-J., et al. (eds.) Robotic Welding, Intelligence and Automation. Lecture Notes in Control and Information Sciences, vol. 299, Springer, Heidelberg (2004)
Bazan, J., et al.: Rough set algorithms in classification problems. In: Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems. Studies in Fuzziness and Soft Computing, vol. 56, Physica-Verlag, New York (2000)
Hu, K., Diao, L., Lu, Y.-c., Shi, C.-Y.: A Heuristic Optimal Reduct Algorithm. In: Leung, K.-S., Chan, L., Meng, H. (eds.) IDEAL 2000. LNCS, vol. 1983, pp. 139–144. Springer, Heidelberg (2000)
Korzen, M., Jaroszewicz, S.: Finding reducts without building the discernibility matrix. In: Proc. of the 5th Int. Conf. on Intelligent Systems Design and Applications (ISDA’05) (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Xu, Z., Zhang, C., Zhang, S., Song, W., Yang, B. (2007). Efficient Attribute Reduction Based on Discernibility Matrix. In: Yao, J., Lingras, P., Wu, WZ., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds) Rough Sets and Knowledge Technology. RSKT 2007. Lecture Notes in Computer Science(), vol 4481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72458-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-540-72458-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72457-5
Online ISBN: 978-3-540-72458-2
eBook Packages: Computer ScienceComputer Science (R0)