Abstract
Finding minimal reducts is a NP-hard problem. For obtain a feasible solution, depth-first-searching is mainly used and a feasible reduct always can be gotten. Whether the feasible reduct is a minimal reduct or not and how far it is to minimal reduct, both are not known. It only gives the information that how many attributes it has and it is a reduct. Based on rough sets reduction theory and the data structure of information system, the least condition attributes to describe the system’s classified characteristics can be known. So an area of searching minimal reducts is decided. By binary search in the area, the minimal reducts can be gotten quickly and doubtlessly.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pawlak, Z.: Rough Sets, Int. J. Comput. Inform. Sci. 11(5), 341–356 (1982)
Pawlak, Z.: Rough Sets and Their Applications. Microcomputer Applications 13(2), 71–75 (1994)
Wong, S.K.M., Ziarko, W.: On Optimal Decision Rules in Decision Tables. Bullet. Polish Acad. Sci. 33, 693–696 (1995)
Xu, N.: The Theory and Technique Research of Attribute Reduction in Data Mining Based on Rough Sets, PhD dissertation, Guangdong University of Technology (2005)
Ni, Z., Cai, J.: Discrete Mathematics. Science Publishes (2002)
Zhang, W., Wu, W., Liang, J., Li, D.: Theory and Method of Rough Sets. Science Publishes (2001)
Guo, J.: Rough set-based approach to data mining, PhD dissertation, Department of Electrical Engineering and Computer Science, Case Wester University, USA (2003)
Hu, X.: Knowledge Discovery in Database: An Attribute-oriented Rough Set Approach (Rules, Decision Matrices), PhD dissertation, The University of Regina, Canada (995)
Wang, J., Miao, D.: Analysis on Attribute Reduction Strategies of Rough Set. J. Comput. Sci. Technol. 13(2), 189–193 (1998)
Shi, Z.: Knowledge Discovery. Tsinghua University Press, Beijing (2002)
Duntsch, I., Gediga, G., Orlowska, E.: Relation Attribute Systems II: Reasoning with Relations in Information Structures. In: Peters, J.F., Skowron, A., Marek, V.W., Orłowska, E., Słowiński, R., Ziarko, W. (eds.) Transactions on Rough Sets VII. LNCS, vol. 4400, pp. 16–35. Springer, Heidelberg (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Xu, N., Liu, Y., Zhou, R. (2008). A Tentative Approach to Minimal Reducts by Combining Several Algorithms. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2008. Communications in Computer and Information Science, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85930-7_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-85930-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85929-1
Online ISBN: 978-3-540-85930-7
eBook Packages: Computer ScienceComputer Science (R0)