KR-DBSCAN: A density-based clustering algorithm based on reverse nearest neighbor and influence space

Density-based clustering is one of the most commonly used analysis methods in data mining and machine learning, with the advantage of locating non-ball-shaped clusters without specifying the number of clusters in advance. However, it has notable shortcomings, such as an inability to distinguish adja...

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Veröffentlicht in:	Expert systems with applications Jg. 186; S. 115763
Hauptverfasser:	Hu, Lihua, Liu, Hongkai, Zhang, Jifu, Liu, Aiqin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 30.12.2021 Elsevier BV
Schlagworte:	Algorithms Cluster expansion Clustering Core object Data mining Datasets Density-based clustering Euclidean geometry Influence space Machine learning Neighborhoods Reverse nearest neighborhood Space density Reverse nearest neighborhood Influence space Cluster expansion Core object Density-based clustering
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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