Title :
One research of clustering algorithm based on rough set and genetic algorithm
Author :
Haixin Wei ; Xiuqing Li
Author_Institution :
Dept. of Inf. Eng., Guilin Univ. of Aerosp. Technol., Guilin, China
Abstract :
This paper integrates rough set theory and adaptive genetic algorithm to propose a new clustering method based on symbols attributes (RAGACA). For each different value, the algorithm adopts the top-down divisive hierarchical clustering strategy and uses RAGA algorithm to dichotomize the data sets step by step until it reaches pre-specified number of cluster, and then output the clustering result. The experimental results show that RACACA has higher accuracy and convergence for the data with symbols attributes.
Keywords :
genetic algorithms; pattern clustering; rough set theory; RAGA algorithm; RAGACA; adaptive genetic algorithm; clustering algorithm; rough set theory; symbols attributes; top-down divisive hierarchical clustering strategy; adaptive; clustering; genetic algorithm; rough set;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526235