Title :
Attribute reduction in inconsistent decision tables based on discernible matrix
Author :
Haiyan, Yu ; Xia, Zhang ; Xiaodong, Qiao ; Yunliang, Zhang
Author_Institution :
Inf. Sci. Support Center, Inst. of Sci. & Tech. Inf. of China, Beijing, China
Abstract :
A method for attributes reduction in inconsistent decision tables is proposed in this paper. The discernible information in inconsistent decision tables is described with discernible vector array. The attribute reduction tree will generate based on the probability of the attributes which discern two objects. The classification of reduction table is same as that of the initial table.
Keywords :
decision tables; decision trees; learning (artificial intelligence); probability; rough set theory; vectors; attribute probability; attribute reduction tree; discernible matrix; discernible vector array; inconsistent decision table; reduction table classification; vector array; Arrays; Finite element methods; Information science; Information systems; Intelligent systems; Set theory; Support vector machine classification; attribute reduction tree; discernible matrix; discernible vector;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554884
