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Even-Sized Clustering with Noise Clustering Method

机译:噪声聚类的均匀聚类

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摘要

Clustering is a method of data analysis without the use of supervised data. Clustering method focusing on cluster size is expected to be useful for task distribution problems and several methods have been proposed. We proposed Fuzzy Even-sized Clustering Based on optimization (FECBO) and COntrolled-sized Clustering Based on Optimization (COCBO) as a method focusing on cluster size. However, these methods have the problem that they are susceptible to noise. It is believed that this issue can be overcome by applying noise clustering method. Noise clustering is a method that it classify noise into noise clusters. In this study, we extend FECBO and COCBO with noise clustering and verify its effectiveness through numerical examples.
机译:聚类是一种不使用监督数据的数据分析方法。期望着重于集群大小的聚类方法对于任务分配问题很有用,并且已经提出了几种方法。我们提出了基于优化的模糊均匀大小聚类(FECBO)和基于优化的联合大小聚类(COCBO)作为关注集群大小的方法。但是,这些方法具有易受噪声影响的问题。相信可以通过应用噪声聚类方法来克服这个问题。噪声聚类是一种将噪声分类为噪声聚类的方法。在这项研究中,我们通过噪声聚类扩展了FECBO和COCBO,并通过数值示例验证了其有效性。

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