DocumentCode
1929690
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
Volume
4
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
1821
Lastpage
1825
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICMLC.2007.4370444
Filename
4370444
Link To Document