Title :
An Attribute Reduct Algorithm Based on Clustering
Author_Institution :
Dept. of Math. & Comput. Sci., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
First, combining the clustering techniques and rough set theory, we put forward an attribute significance algorithm of continuous domain decision table. Then, an attribute reduct algorithm is obtained according to significance of attribute. At last, the effectiveness of this attribute reduct algorithm is verified through a concrete example.
Keywords :
decision tables; pattern clustering; rough set theory; attribute reduct algorithm; continuous domain decision table; rough set theory; Cities and towns; Clustering algorithms; Concrete; Fuzzy systems; Inference algorithms; Logic; Mathematics; Rough sets; Seminars; Set theory; attribute reduct; clustering; fuzzy sets; rough sets;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.570
