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ADAPTIVE HIERARCHICAL CLUSTERING ALGORITHM

机译:自适应层次聚类算法

摘要

Systems and methods for clustering a plurality of feature vectors. A hierarchical clustering algorithm is performed on the plurality of feature vectors to provide a plurality of clusters and a cluster similarity measure for each cluster representing the quality of the cluster. Each cluster of the plurality of clusters with a cluster similarity measure meeting a threshold value is accepted. A clustering algorithm is performed on each cluster that fails to meet the threshold value to provide a set of subclusters each having an associated cluster similarity measure. Each subcluster having a cluster similarity measure meeting the threshold value is accepted.
机译:用于聚类多个特征向量的系统和方法。在多个特征向量上执行分层聚类算法,以提供多个聚类,并为代表聚类质量的每个聚类提供聚类相似性度量。具有簇相似性度量满足阈值的多个簇中的每个簇被接受。在每个不满足阈值的集群上执行聚类算法,以提供一组子集群,每个子集群都具有关联的集群相似性度量。具有集群相似性度量满足阈值的每个子集群都将被接受。

著录项

  • 公开/公告号US2014037214A1

    专利类型

  • 公开/公告日2014-02-06

    原文格式PDF

  • 申请/专利权人 VINAY DEOLALIKAR;HERNAN LAFFITTE;

    申请/专利号US201213562524

  • 发明设计人 VINAY DEOLALIKAR;HERNAN LAFFITTE;

    申请日2012-07-31

  • 分类号G06K9/62;G06K9/48;

  • 国家 US

  • 入库时间 2022-08-21 16:01:50

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