DocumentCode :
498389
Title :
A New Method of Attribute Reduction Based on Gamma Coefficient
Author :
Bai, Jiang ; Wei, Li-Li
Author_Institution :
Sch. of Math. & Comput. Sci., Ningxia Univ., Yinchuan, China
Volume :
2
fYear :
2009
fDate :
19-21 May 2009
Firstpage :
370
Lastpage :
373
Abstract :
In this paper, nonparametric method in statistics is introduced to analyze the reduction of ordinal attributes. Firstly,Goodman-Kruskal gamma coefficient, which is used to measuring the correlativity between ordinal variables in statistics, is now used as a new measure of correlativity between ordinal attribute sets after modifying it properly. Then, based on this new measure, a new method of attribute reduction for ordered decision tables is presented, and some connections between the method and the rough set theory about attribute reduction can be found. Furthermore, the numerical experiments show that the nonparametric statistical method we proposed is feasible and efficient for both consistent and inconsistent ordered decision tables.
Keywords :
decision tables; gamma distribution; rough set theory; gamma coefficient; nonparametric statistical method; ordered decision tables; ordinal attribute sets; ordinal attributes reduction; ordinal variables; rough set theory; Computer science; Databases; Information systems; Intelligent systems; Machine learning; Mathematics; Rough sets; Set theory; Statistical analysis; Statistics; Attribute Reduction; Gamma Coefficient; Rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
Type :
conf
DOI :
10.1109/GCIS.2009.212
Filename :
5209401
Link To Document :
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