Title :
Search the Optimal Preference of Affinity Propagation Algorithm
Author :
Zhong, Yi ; Zheng, Ming ; Wu, Jianan ; Shen, Wei ; Zhou, You ; Zhou, Chunguang
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Abstract :
In order to improve the clustering quality of the Affinity Propagation algorithm further and get more accurate number of clusters, this paper proposed a novel algorithm based on the Particles Swarm Optimization, which used In-Group Proportion index as fitness function to search the optimal preference of Affinity Propagation algorithm. Experimental results show that the predicted results had been tested with the novel proposed algorithm and the better results had been achieved.
Keywords :
particle swarm optimisation; pattern clustering; affinity propagation algorithm; clustering analysis; clustering quality; fitness function; in-group proportion index; optimal preference; particles swarm optimization; Algorithm design and analysis; Clustering algorithms; Heart; Indexes; Iris; Optimization; Prediction algorithms; Affinity Propagation Algorithm; In-Group Proportion index; Particles Swarm Optimization; the optimal preference;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2012 Fifth International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-1-4673-0470-2
DOI :
10.1109/ICICTA.2012.83
