Relative density-based clustering algorithm for identifying diverse density clusters effectively

Clustering is an important part of data mining. The existing clustering algorithm failed in the data set with uneven density distribution. In this paper, we propose a novel clustering algorithm relative density-based clustering algorithm for identifying diverse density clusters effectively called ID...

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Vydáno v:	Neural computing & applications Ročník 33; číslo 16; s. 10141 - 10157
Hlavní autoři:	Wang, Yuying, Yang, Youlong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.08.2021 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Clustering Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data mining Data Mining and Knowledge Discovery Data points Datasets Density Density distribution Image Processing and Computer Vision Original Article Outliers (statistics) Probability and Statistics in Computer Science Allocation strategy nearest neighbors Relative density Density-based clustering
ISSN:	0941-0643, 1433-3058
On-line přístup:	Získat plný text
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