DocumentCode :
2256645
Title :
Sample selection with rough set
Author :
Chen, De-Gang ; Zhang, Xiao ; Tsang, E.C.C. ; Yang, Yong-ping
Author_Institution :
Dept. of Math. & Phys., North China Electr. Power Univ., Beijing, China
Volume :
1
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
291
Lastpage :
295
Abstract :
In this paper sample selection with rough set is proposed in order to compress the discernibility matrix of a decision table so that only minimal elements in the discernibility matrix are employed to find reducts. First relative discernibility relation of conditional attribute is defined, indispensable and dispensable conditional attributes are characterized by their relative discernibility relations and key object pair set is defined for every conditional attribute. With the key object pair sets all the sample selections can be found. An example is employed in this paper to illustrate our idea of sample selection with rough set.
Keywords :
decision tables; matrix algebra; rough set theory; conditional attribute; decision table; discernibility matrix; relative discernibility relation; rough set; sample selection; Approximation methods; Boolean functions; Cybernetics; Information systems; Machine learning; Rough sets; Attribute reduction; Rough set; Sample core; Sample selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
Type :
conf
DOI :
10.1109/ICMLC.2010.5581051
Filename :
5581051
Link To Document :
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