Title :
A Classification Algorithm of Continuous Domain Decision Table
Author_Institution :
Dept. of Math. & Comput. Sci., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
First, the definition of similarity degree of objects in continuous domain decision table is given; then, according to fuzzy clustering, an attribute reduct and attribute significance algorithm of continuous domain decision table is put forward; thirdly, a classification algorithm is proposed according to the principle of maximum membership degree; at last, the validity of this classification algorithm is accounted for through an example.
Keywords :
decision tables; fuzzy set theory; pattern classification; pattern clustering; classification algorithm; continuous domain decision table; fuzzy clustering; maximum membership degree; Cities and towns; Classification algorithms; Clustering algorithms; Decision support systems; Fuzzy systems; Machine learning; Machine learning algorithms; Mathematics; Pattern recognition; Set theory; attribute value; classification; decision class; membership degree; rough set;
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.2009.571
