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A Clustering Method Based on the Modified RS Validity Index

机译:基于改进的RS有效性指标的聚类方法

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摘要

This paper describes a new method to the determination of the optimal number of well-separable clusters in data sets. The determination of this parameter is necessary for many clustering algorithms to define the naturally existing clusters correctly. In the presented method the idea of the agglomerative hierarchical clustering has been used, and the modified RS cluster validity index has been applied. In the first phase of the method, clusters are created due to the idea of hierarchical clustering. Then, for the optimal number of clusters the k-means algorithm is performed. The method has been used for multidimensional data, and the received results confirm very good performances of the proposed method.
机译:本文介绍了一种确定数据集中最佳可分簇数的新方法。该参数的确定对于许多聚类算法正确定义自然存在的聚类是必要的。在提出的方法中,使用了聚集层次聚类的思想,并且已经应用​​了改进的RS聚类有效性指数。在该方法的第一阶段,由于层次聚类的想法而创建了聚类。然后,对于最佳数目的群集,执行k均值算法。该方法已用于多维数据,接收到的结果证实了该方法的良好性能。

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