数据库扫描
聚类分析
计算机科学
层次聚类
比例(比率)
数据挖掘
人工智能
CURE数据聚类算法
相关聚类
量子力学
物理
作者
Leland McInnes,John Healy
标识
DOI:10.1109/icdmw.2017.12
摘要
We present an accelerated algorithm for hierarchical density based clustering. Our new algorithm improves upon HDBSCAN*, which itself provided a significant qualitative improvement over the popular DBSCAN algorithm. The accelerated HDBSCAN* algorithm provides comparable performance to DBSCAN, while supporting variable density clusters, and eliminating the need for the difficult to tune distance scale parameter. This makes accelerated HDBSCAN* the default choice for density based clustering. Library available at: https://github.com/scikit-learn-contrib/hdbscan
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