Title :
A Discussion of Attribute Reduction in Fuzzy Rough Sets Using Support Vector Machine
Author :
Tsang, Eric C C ; Chen, Degang ; Zhao, Suyun ; He, Qiang
Author_Institution :
Hong Kong Polytech. Univ., Kowloon
Abstract :
This paper mainly focuses on the attribute reduction in fuzzy rough sets. An algorithm using discernibility matrix to compute all the attribute reductions is developed. After reducing the attributes, we introduce Support Vector Machine (SVM) as a classification technique to test the knowledge representation ability of attribute reduction. The numerical results show that the attribute reduction with fuzzy rough sets contains the same information as the original one.
Keywords :
data analysis; data reduction; fuzzy set theory; knowledge representation; matrix algebra; pattern classification; rough set theory; support vector machines; SVM; attribute reduction; data analysis; discernibility matrix; fuzzy rough set; knowledge representation; pattern classification; support vector machine; Cybernetics; Fuzzy sets; Helium; Knowledge representation; Mathematics; Rough sets; Set theory; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
DOI :
10.1109/ICSMC.2006.384650
