文章基本信息

标题：An Unsupervised Classification of Cancer Genes Using Genetic Algorithm
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作者：Helan Cynthiya Y. ; Anusha M. ; J. G. R. Sathiaseelan 等
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：7
页码：3202-3206
出版社：Shri Pannalal Research Institute of Technolgy
摘要：K-means algorithm is a standard unsupervised clustering technique that helps in successful termination of problem in relatively efficient manner. Though K-means is simple and easy to implement, it fails to find the most optimal configuration as the initialization of clusters at the beginning is difficult and sensitive to cluster centers. To improve the efficiency of K-means, Evolutionary Algorithm, like Genetic Algorithm is used for solving local optima obtained from the former. The algorithm EKMGA is proposed in this paper, which finds the fittest value of the chromosome at the minimum number of generation with K-means selection of clusters. The algorithm EKMGA is tested using two different cancer datasets that were taken from UCI repository. The implementation is done using Java code and Weka tool.
关键词：Clustering; K-means Algorithm; Genetic algorithm; Enhanced K-means Genetic Algorithm