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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近邻的数据聚类方法,该方法根据数据点的K近邻的最大半径,即根据密度,对要聚类的数据点进行升序排序,并执行在以升序对数据点进行排序之后将数据点进行第一次遍历,以将符合统计相似性的数据点合并到同一聚类中;然后根据聚类时所需的规模,以较小的聚类密度对数据点进行第二次遍历,找出所有噪声点并将非噪声点合并到最近的大密度聚类中,从而实现数据聚类,它的优点是无需预先设置聚类的数量,也不需要知道数据的概率分布以及设置参数的便利性。

著录项

  • 公开/公告号US2019251121A1

    专利类型

  • 公开/公告日2019-08-15

    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;G06K9/62;G06F17/18;

  • 国家 US

  • 入库时间 2022-08-21 12:10:28

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