Rough Set Theory Analysis on Decision Subdivision
The degree of subdivision of the decision attribute value influences upon the accuracy of approximation classification, the approximation quality of rules, the core attributes and the information entropy in decision systems based on rough set theory. The finer the decision attribute discretization of a decision table is, the less the accuracy of approximation classification, the approximation quality of rules, and information entropy are on any condition attribute set. Meanwhile, if the attribute values of decision attributes are divided into finer values, then the core attributes set obtained from the finer decision table must include the core attributes set obtained from the previous decision table. These conclusions are proved theoretically. So the discrete degree of decision attributes should be chosen properly. The research is helpful to attribute reduction and enhancing confidences of decision rules.
KeywordsDecision Rule Information Entropy Approximation Quality Decision Table Decision Attribute
Unable to display preview. Download preview PDF.
- 1.Pawlak, Z., Slowinski, R.: Rough set approach to multi-attribute decision analysis. Institute of Computer Science, Warsaw University of Technology, Tech Report: 36 (1993)Google Scholar
- 2.Nguyen, H.S., Skowron, A.: Quantization of real values attributes, rough set and boolean reasoning approaches. In: Proc. of the Second Joint Annual Conference on Information Science, Wrightsville Beach, NC, pp. 34–37 (1995)Google Scholar
- 3.Nguyen, S.H., Nguyen, H.S.: Some Efficient Algorithms for Rough Set Methods. In: Proc. of the Conference of Information Processing and Management of Uncertainty in Knowledge-Based Systems, Granada, Spain, pp. 1451–1456 (1996)Google Scholar
- 4.Knowledge Systems Group.: Rosetta Technical Reference Manual (1999)Google Scholar
- 5.Yingshan, Z.: Theory of Multilateral Matrix. Chinese Statistic Press, Peking (1993) (in Chinese)Google Scholar