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Data clustering method and apparatus based on k-nearest neighbor and computer readable storage medium

机译:基于k - 最近邻和计算机可读存储介质的数据聚类方法和装置

摘要

The present disclosure provides a data clustering method based on K-nearest neighbor, which sorts data points to be clustered in ascending order according to the maximum radiuses of K-nearest neighbors of the data points, that is, according to the density, and perform the first pass across the data points after sorting the data points in ascending order to incorporate the data points that conform to the statistical similarity into the same cluster; then perform the second pass across the data points with smaller cluster density according to the scale required during the clustering to find out all noise points and incorporate non-noise points into the nearest large-density cluster, so as to realize data clustering, which has the benefits of no need to preset the number of clusters and know the probability distribution of the data and convenience to set parameters.
机译:本公开提供了一种基于K-CORMATE邻居的数据聚类方法,其根据数据点的k-reald邻居的最大半径对数据点进行排序以按升序群集,即,根据密度和执行 在按升序排序数据点之后,在数据点进行排序以将符合统计相似性的数据点包含到同一集群中的数据点; 然后根据群集期间所需的刻度来执行具有较小群集密度的数据点的第二传递,以查找所有噪声点并将非噪声点包含到最接近的大密度集群中,以实现数据集群 无需预设集群数量,并知道数据的概率分布和设置参数的便利性。

著录项

  • 公开/公告号US11210348B2

    专利类型

  • 公开/公告日2021-12-28

    原文格式PDF

  • 申请/专利权人 HUIZHOU UNIVERSITY;

    申请/专利号US201916396682

  • 发明设计人 JINQIU HUANG;DEMING XU;CHANGLIN WAN;

    申请日2019-04-27

  • 分类号G06F16/906;G06F17/18;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-24 23:04:18

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