文章基本信息

标题：Automatic Clustering with Single Optimal Solution
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作者：Karteeka Pavan K ; Allam Appa Rao ; A.V. Dattatreya Rao 等
期刊名称：Computer Engineering and Intelligent Systems
印刷版ISSN：2222-1727
电子版ISSN：2222-2863
出版年度：2011
卷号：2
期号：4
页码：149-161
语种：English
出版社：International Institute for Science, Technology Education
摘要：Determining optimal number of clusters in a dataset is a challenging task. Though some methods are available, there is no algorithm that produces unique clustering solution. The paper proposes an Automatic Merging for Single Optimal Solution (AMSOS) which aims to generate unique and nearly optimal clusters for the given datasets automatically. The AMSOS is iteratively merges the closest clusters automatically by validating with cluster validity measure to find single and nearly optimal clusters for the given data set. Experiments on both synthetic and real data have proved that the proposed algorithm finds single and nearly optimal clustering structure in terms of number of clusters, compactness and separation.