文章基本信息

标题：Comparison of Various Clustering Algorithms
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作者：Garima Sehgal ; Dr. Kanwal Garg
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：3
页码：3074-3076
出版社：TechScience Publications
摘要：A comparative study of clustering algorithms across three different datasets is performed. The algorithms under investigation are partitioning based i.e K-means, Farthest First, Expectation maximization and Non Partitioning based i.e Density based, Hierarchical based and Cobweb. All these algorithms are compared according to the factors size of the dataset, number of clusters and time taken to form clusters. Performance of clustering algorithms are compared using clustering tool WEKA(version 3.7.10).
关键词：K-means algorithm; Farthest First algorithm;Expectation Maximization algorithm; Density based algorithm;Hierarchical based algorithm; Cobweb algorithm; WEKA tool