Title :
A new reduction model of inconsistent decision table
Author :
Jiang, Si-Yu ; Lu, Yan-sheng
Author_Institution :
Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., China
Abstract :
Two reduction definitions have been introduced in classical rough set theory. One is an algebra definition, and the other is an information definition. However, the two definitions both regard accuracy of rules as criteria of reduction and the former only cares accuracy of deterministic rules, the latter cares accuracy of entire rules. Therefore, for inconsistent decision table, the reduction results that we obtain by using the two definitions respectively could be different. This paper presents a new reduction model that its criteria of reduction combine accuracy and coverage of rules. Correspondingly, this paper proposes two new reduction definitions under the new model. By analyzing and testing, for inconsistent decision table, the reduction results that we obtain by using the two new definitions respectively are uniform. In addition, the reduction results with respect to the new reduction model may arrive at a better effect.
Keywords :
data reduction; decision tables; rough set theory; algebra definition; attribute reduction; decision entropy; deterministic rules; inconsistent decision table; information definition; reduction model; rough set theory; Algebra; Computer science; Cybernetics; Educational institutions; Entropy; Laboratories; Machine learning; Set theory; Software engineering; Testing; attribute reduction; average information; decision entropy; rough set;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527257