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K-means clustering based data mining system and method using the same

机译:基于K-Means基于集群的数据挖掘系统和方法使用相同

摘要

A method of performing K-means clustering by a data mining system is provided. The method includes generating a plurality of initial buckets by dividing data including a plurality of points each being expressed in coordinate information, reflecting a count noise in a number of points included in each of the initial buckets and then generating a plurality of new buckets by dividing at least one initial bucket among the initial buckets based on a first threshold and a second threshold, generating a plurality of final buckets from the plurality of initial buckets or the plurality of new buckets, generating a histogram including section information for each of the final buckets and a number of points included in each of the final buckets in which the count noise is reflected, and performing K-means clustering on the histogram based on a number of clusters.
机译:提供了通过数据挖掘系统执行K-Means聚类的方法。该方法包括通过划分包括在坐标信息中表达的多个点的数据来生成多个初始桶,反映包括在每个初始桶中的每个点中的计数噪声,然后通过划分产生多个新桶基于第一阈值和第二阈值的初始桶中的至少一个初始桶,从多个初始桶或多个新桶生成多个最终桶,从而生成包括每个最终桶的部分信息的直方图和许多包含在每个最终桶中的点,其中计数噪声反映,并且基于多个簇在直方图上执行k-means群集。

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