DocumentCode
387533
Title
Optimal decision rules based on inclusion degree theory
Author
Mi, Ju-Sheng ; Zhang, Wen-xiu ; Wu, Wei-Zhi
Author_Institution
Fac. of Sci., Xi´´an Jiaotong Univ., China
Volume
3
fYear
2002
fDate
2002
Firstpage
1223
Abstract
The purpose of the paper is to establish knowledge reductions in inconsistent decision tables. Based on rough set theory, the concepts of upper and lower approximation reductions are introduced. Their relationships are investigated. With the theory of inclusion degree, the maximum distribution reduction and the optimal maximum distribution rules are also presented, which are more useful in making brief decision rules from inconsistent information systems. Then a new knowledge discovery approach is established.
Keywords
data mining; decision making; equivalence classes; rough set theory; approximation reductions; brief decision rules; inclusion degree theory; inconsistent decision tables; inconsistent information systems; knowledge discovery; knowledge reductions; maximum distribution reduction; optimal decision rules; optimal maximum distribution rules; rough set theory; Cybernetics; Information science; Information systems; Knowledge representation; Machine learning; Mathematics; Noise reduction; Oceans; Reflection; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN
0-7803-7508-4
Type
conf
DOI
10.1109/ICMLC.2002.1167395
Filename
1167395
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