Title :
Attribute Reduction in Information Systems via Oriented Association Coefficient
Author_Institution :
Sch. of Math. & Comput. Sci., Ningxia Univ., Yinchuan, China
Abstract :
Rough set data analysis has recently become a routine method in categorical data analysis. One of the important problems in rough set theory is attribute reduction. In this paper, the statistic named oriented association coefficient among attributes of information systems is introduced, which measures the non-linear relationships between qualitative variables. Based on this statistic, we present a new discriminant theorem of attribute reduction in information systems. Furthermore, experiments show that our approach is feasible and efficient.
Keywords :
data analysis; data mining; information systems; rough set theory; statistical analysis; attribute reduction; categorical data analysis; discriminant theorem; information system; oriented association coefficient; qualitative variable; rough set data analysis; statistical analysis; Bayesian methods; Computer science; Data analysis; Information analysis; Information systems; Mathematics; Probability; Set theory; Statistical analysis; Statistics; attribute reduction; categorical data; information systems; oriented association coefficient; rough set;
Conference_Titel :
Web Mining and Web-based Application, 2009. WMWA '09. Second Pacific-Asia Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3646-0
DOI :
10.1109/WMWA.2009.56