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The Algorithm of Extracting the Certain and Uncertain Rule

Conference paper
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Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 165)

Abstract

A new algorithm of the rule extraction is put forward to overcome the limitation of tradition rule extraction. The rule extraction of decision information systems can be obtained directly from the decision classes, and the class table of information system can be generated by cluster analysis theory. It simplifies the original information system and reduces the scope of rule extraction. The certain and uncertain basic decision rules can be directly generated by rough sets theory, and the basic decision rule database will be generated as well. Simultaneously, any certain rules can generate from the basic decision rules have been proved. The description of algorithm is given and the efficiency of the algorithm is analyzed as well.

Keywords

rough sets decision tables information system decision classes 

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References

  1. 1.
    Pawlak, Z.: Rough sets. International Journal of Computer and Information Science 11(2), 341–356 (1982)MathSciNetzbMATHCrossRefGoogle Scholar
  2. 2.
    Swinizrski, R.W., Skowron, A.: Rough sets methods in feature selection and recognition. Pattern Recognition Letters 24, 833–849 (2003)CrossRefGoogle Scholar
  3. 3.
    Kerber, R.: Chimerge: Discretization of numeric attributes. In: Proc.10th National Conference on Artificial Intelligence, pp. 123–128. Impress (1992)Google Scholar
  4. 4.
    Xi, J., Ou, Y.W.M.: Clustering based algorithm for best discretizing continuous valued attributes. Mini-micro Systems 21(10), 1025–1027 (2000)Google Scholar
  5. 5.
    Xu, E., Gao, X.X.D., Tan, W.D., et al.: Discretization algorithm based on super-cube and information entropy. Journal of University of Science and Technology 27(6), 760–763 (2005)zbMATHGoogle Scholar
  6. 6.
    Shen, L., Loh, H.T.: Applying rough sets to market timing decisions. Decision Support Systems 37, 583–597 (2004)CrossRefGoogle Scholar
  7. 7.
    Huang, C.-C., Tseng, T.-L.B.: Rough sets approach tocase-based reasoning applition. Expert Systems with Applications 26, 369–385 (2004)CrossRefGoogle Scholar
  8. 8.
    Zhang, W.X., Wu, W.Z., Liang, J.: Rough sets theory and method, pp. 206–212. Science press, Beijing (2001)Google Scholar
  9. 9.
    Zhou, J., Zhang, Q.L., Chen, W.S.: A method about rough sets being fuzzed by using equivalence relation. Northeastern University (Natural Science) 25(8), 731–733 (2004)MathSciNetGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Computer CenterLiaoning University of TechnologyJinzhouChina

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