Ordered Decision Rules Extraction Algorithm Based on Granular Computing
XU Jiu-Cheng1, SHI Jin-Ling1,2, ZHANG Qian-Qian1
1.Key Laboratory for Intelligent Information Processing, College of Computer and Information Technology, Henan Normal University, Xinxiang 453007 2.International School of Education, Xuchang University, Xuchang 461000
Abstract An algorithm for extracting ordered decision rules based on granular computing is proposed to extract the most compact ordered decision rule from the ordered decision table. Firstly, an ordered decision table is transformed into the form of the ordered matrix by defining the concept of the ordered matrix and the λ-rank granular base about ordered decision table. Then, the ordered matrix and granular bases are studied and analyzed from different granularity level. Moreover, the algorithm is implemented for extracting the ordered decision rules, which satifies user expectation, as many as possible from the lower rank granular base with the search criteria of the lowest limitation of rule coverage and confidence. Finally, the validity for the algorithm is proved by analyzing examples.
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2009, Vol. 22 
