A robust density peaks clustering algorithm with density-sensitive similarity

Density peaks clustering (DPC) algorithm is proposed to identify the cluster centers quickly by drawing a decision-graph without any prior knowledge. Meanwhile, DPC obtains arbitrary clusters with fewer parameters and no iteration. However, DPC has some shortcomings to be addressed before it is wide...

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Vydané v:	Knowledge-based systems Ročník 200; s. 106028
Hlavní autori:	Xu, Xiao, Ding, Shifei, Wang, Lijuan, Wang, Yanru
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 20.07.2020 Elsevier Science Ltd
Predmet:	Algorithms Automatic clustering Clustering Clustering validity index Datasets Decisions Density Density-sensitive similarity DPC algorithm Manifolds Parameter sensitivity Prior knowledge Robustness Similarity Density-sensitive similarity Clustering validity index Automatic clustering DPC algorithm
ISSN:	0950-7051, 1872-7409
On-line prístup:	Získať plný text
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