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An optimized farthest first clustering algorithm

机译:优化的最远的第一聚类算法

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Data mining is the process of analyzing data from different viewpoints and summarizing it into useful information. Clustering is the process of grouping of similar objects together. The group of the objects is called the cluster which contains similar objects compared to objects of the other cluster. Different clustering algorithm can be used according to the behavior of data. Farthest first algorithm is suitable for the large dataset but it creates the non-uniform cluster. The paper forms optimization of farthest first algorithm of clustering resulting uniform clusters.
机译:数据挖掘是从不同的视点分析数据的过程,并将其概括为有用的信息。聚类是将类似对象分组在一起的过程。与其他群集的对象相比,对象的组称为包含类似对象的群集。可以根据数据的行为使用不同的聚类算法。最远的第一算法适用于大型数据集,但它会创建非统一群集。本文形成了统一簇最远的群体群体算法的优化。

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