Title :
An Evolutionary Computation Based on GA Optimal Clustering
Author :
Cheng, Ching-Hsue ; Wei, Liang-Ying
Author_Institution :
Nat. Yunlin Univ. of Sci. & Technol., Touliu
Abstract :
Clustering analysis is utilized to analyze the clustering phenomenon occurred to the data structure. This paper proposes a new GA-based clustering method based on the stopping conditions which consider the clustering accuracy for datasets. From experiment results using the UCI datasets of WINE and IRIS, which indicate that the accuracy of the proposed method is better than the listing methods, and the speed of convergence is very fast.
Keywords :
convergence; genetic algorithms; pattern clustering; GA optimal clustering; IRIS; UCI datasets; WINE; clustering analysis; evolutionary computation; Algorithm design and analysis; Biological cells; Clustering algorithms; Clustering methods; Cybernetics; Delta modulation; Evolutionary computation; Information analysis; Machine learning; Partitioning algorithms; Clustering analysis; Data mining; Genetic algorithms;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370444
