Abstract
This paper is devoted to the discussion of the relationship among some reduction approaches of information systems. It is proved that the distribution reduction and the entropy reduction are equivalent, and each distribute reduction is a d reduction. Furthermore, for consistent information systems, the distribution reduction, entropy reduction, maximum distribution reduction, distribute reduction, approximate reduction and d reduction are all equivalent.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Pawlak, Z.: Rough Sets. International Journal of Computer and Information Science 11, 341–356 (1982)
Pawlak, Z. (ed.): Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers, Boston (1991)
Marczewski.: A General Scheme of Independence in Mathematics. Bulletin de L Academie Polonaise des Sciences–Serie des Sciences Mathematiques Astronomiques et Physiques. 6, 731–736 (1958)
Wang, G., Yu, Y., Yang, H.: Decision Table Reduction Based on Conditional Information Entropy. Chinese Journal of Computers 25, 759–766 (2002) (in Chinese)
Zhang, W.X., Mi, J.S., Wu, W.Z.: Knowledge Reductions in Inconsistent Information Systems. Chinese Journal of Computers 26, 12–18 (2003) (in Chinese)
Skowron, A., Rauszer, C.: The Discernibility Matrices And Functions in Information System. Intelligent Decision Support Handbook of Applications and Advances of the Rough Sets Theory. Kluwer Academic Publishers, Dordrecht (1992)
Kryszkiewicz.: Comparative Study of Alternative Type of Knowledge Reduction in Inconsistent Systems. International Journal of General Systems. 16, 105–120 (2001)
Beynon, M.: Reducts within The Variable Precision Rough Set Model: A Further Investigation. European Journal of Operational Research 134, 592–605 (2001)
Quafatou, M.: RST: A Generalization of Rough Set Theory. Information Sciences 124, 301–316 (2000)
Zheng, P., Keyun, Q.: Obtaining Decision Rules And Combining Evidence Based on Modal Logic. Progress in Natural Science 14, 501–508 (2004) (in chinese)
Zheng, P., Keyun, Q.: Intuitionistic Special Set Expression of Rough Set And Its Application in Reduction of Attributes. Pattern Recognition and Artificial Intelligence 17, 262–266 (2004) (in chinese)
Slowinski, R., Zopounidis, D.A.I.: Prediction of Company Acquisition in Greece by Means of The Rough Set Approach. European Journal of Operational Research 100, 1–15 (1997)
Jusheng, M., Weizhi, W., Wenxiu, Z.: Approaches to Knowledge Reduction Based on Variable Precision Rough Set Model. Information Sciences 159, 255–272 (2004)
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
Qin, K., Pei, Z., Du, W. (2005). The Relationship Among Several Knowledge Reduction Approaches. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_154
Download citation
DOI: https://doi.org/10.1007/11539506_154
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28312-6
Online ISBN: 978-3-540-31830-9
eBook Packages: Computer ScienceComputer Science (R0)