DocumentCode :
1563334
Title :
An Approach to Reduction Based on Correlation Information Vector
Author :
Pei, XiaoBing ; Wang, Yuanzhen
Author_Institution :
Dept. of Comput. Sci., Huazhong Univ. of Sci. & Technol., Hubei
Volume :
1
fYear :
2005
Firstpage :
236
Lastpage :
239
Abstract :
Attribute reduction is one of the basic contents in rough set theory. And it has been proved that computing the optimal attribute reduction is NP-complete. In this paper, a new concept of correlation information vector is introduced in inconsistent information system, the judgment theorem with respect to attribute reduction is obtained and the significance of attributes is defined in information system, from which a complete polynomial heuristic algorithm for the optimal reduction is proposed. Finally, we also show the results of the algorithm by an illustrative example
Keywords :
computational complexity; rough set theory; NP-complete; attribute reduction; correlation information vector; judgment theorem; optimal reduction; polynomial heuristic algorithm; rough set theory; Computer science; Data mining; Frequency; Heuristic algorithms; Information systems; Mathematics; NP-complete problem; Polynomials; Region 5; Set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
Type :
conf
DOI :
10.1109/ICNNB.2005.1614605
Filename :
1614605
Link To Document :
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