Title :
Attributes reduction based on important degree of attributes in incomplete information system
Author :
Yang, Jilin ; Wei, Dongmei ; Liu, Qiong ; Hai, Yufeng
Author_Institution :
Sch. of Math., Southwest Jjiaotong Univ., Chengdu, China
Abstract :
In incomplete information systems, based on similarity relation, a method of attributes reduction is discussed in this paper. Relative important degree of attributes is defined. Important degree of attributes is obtained by using the OWA operator to aggregate relative important degree of attributes. Due to finding attributes reduction in accordance with the reorder of attributes which identified by important degree of attributes, the advantage of our method is to reduce the search space of attribute reduction and avoid blindness. Finally, the specific example shows our method is effective.
Keywords :
information systems; rough set theory; OWA operator; attribute reduction; finding attributes reduction; incomplete information system; search space; similarity relation; Aggregates; Blindness; Helium; Information systems; Machine learning; Mathematics; Open wireless architecture; Rough sets; Set theory; Uncertainty;
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2009.5277286