Title :
Genetic Algorithm Based Clustering: A Survey
Author :
Sheikh, Rahila H. ; Raghuwanshi, M.M. ; Jaiswal, Anil N.
Author_Institution :
RCERT, Chandrapur
Abstract :
This survey gives state-of-the-art of genetic algorithm (GA) based clustering techniques. Clustering is a fundamental and widely applied method in understanding and exploring a data set. Interest in clustering has increased recently due to the emergence of several new areas of applications including data mining, bioinformatics, web use data analysis, image analysis etc. To enhance the performance of clustering algorithms, Genetic Algorithms (GAs) is applied to the clustering algorithm. GAs are the best-known evolutionary techniques. The capability of GAs is applied to evolve the proper number of clusters and to provide appropriate clustering. This paper present some existing GA based clustering algorithms and their application to different problems and domains.
Keywords :
data mining; genetic algorithms; pattern classification; pattern clustering; unsupervised learning; data clustering algorithm; data mining; evolutionary technique; genetic algorithm; unsupervised pattern classification; Bioinformatics; Biological cells; Clustering algorithms; Data analysis; Data mining; Genetic algorithms; Genetic engineering; Genetic mutations; Image analysis; Partitioning algorithms; GA based clustering; Genetic algorithm; clustering algorithms; pattern recognition;
Conference_Titel :
Emerging Trends in Engineering and Technology, 2008. ICETET '08. First International Conference on
Conference_Location :
Nagpur, Maharashtra
Print_ISBN :
978-0-7695-3267-7
Electronic_ISBN :
978-0-7695-3267-7
DOI :
10.1109/ICETET.2008.48