Adaptive density peak clustering based on K-nearest neighbors with aggregating strategy

Recently a density peaks based clustering algorithm (dubbed as DPC) was proposed to group data by setting up a decision graph and finding out cluster centers from the graph fast. It is simple but efficient since it is noniterative and needs few parameters. However, the improper selection of its para...

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Veröffentlicht in:	Knowledge-based systems Jg. 133; S. 208 - 220
Hauptverfasser:	Yaohui, Liu, Zhengming, Ma, Fang, Yu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.10.2017 Elsevier Science Ltd
Schlagworte:	Adaptive algorithms Aggregating Algorithms Clustering Clustering algorithm Clusters Density Density peaks Experiments K-nearest neighbors K-nearest neighbors Density peaks Clustering algorithm Aggregating
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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