DocumentCode :
458856
Title :
Weighted Rough Set Model
Author :
Ma, Tinghuai ; Tang, Meili
Author_Institution :
Dept. of Comput. Sci., Nanjing Univ. of Info. & Sci. Tech.
Volume :
1
fYear :
2006
fDate :
16-18 Oct. 2006
Firstpage :
481
Lastpage :
485
Abstract :
Equal set is the most important concept in rough set. In classic rough set model, the equality is strong, must be very precise. But strong equality cause inapplicable due to data noise. Variable precision rough set model solve the data noise by introducing an error-tolerated factor. But there are no weighted factors in knowledge system. Especially, after data cleaning, rules those have same form will be unite to one rule. But objects have different importance is more close to actually application. In this paper, weighted rough set (WRS) model is provided. WRS is based on variable precision rough set (VPRS) model. This model not only considers the noise tolerant capability, but also considers the objects´ importance. In weighted rough set model, some basic concepts are redefined. Also, reduction definition is provided. At last, from the experiments, weighted rough set model´s characters are got
Keywords :
rough set theory; data cleaning; reduction definition; variable precision rough set model; weighted rough set model; Algebra; Cleaning; Computer science; Fuzzy set theory; Knowledge based systems; Logic; Probability; Set theory; Statistics; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
Type :
conf
DOI :
10.1109/ISDA.2006.280
Filename :
4021486
Link To Document :
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