DocumentCode
1627954
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
fYear
2009
Firstpage
621
Lastpage
625
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location
Jeju Island
ISSN
1098-7584
Print_ISBN
978-1-4244-3596-8
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2009.5277286
Filename
5277286
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