文章基本信息

标题：A Genetic Algorithm Approach for Clustering
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作者：Mamta Mor ; Poonam Gupta ; Priyanka Sharma 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：6
页码：6442-6447
出版社：IJECS
摘要：The paper deals with the applicability of GA to clustering and compares it with the standard K-means clustering technique. Kmeansclustering results are extremely sensitive to the initial centroids, so many a times it results in sub-optimal solutions. On the other handthe GA approach results in optimal solutions and finds globally optimal disjoint partitions. Fitness calculated on the basis of intra-clusterand inter-cluster distance is the performance evaluation standard in this paper. The experimental results show that the proposed GA is moreeffective than K-means and converges to more accurate clusters.
关键词：clustering; genetic algorithm; k-means; fitness function