A spectral clustering algorithm based on attribute fluctuation and density peaks clustering algorithm

Spectral clustering (SC) has become a popular choice for data clustering by converting a dataset to a graph structure and then by identifying optimal subgraphs by graph partitioning to complete the clustering. However, k-means is taken at the clustering stage to randomly select the initial cluster c...

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Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 53; číslo 9; s. 10520 - 10534
Hlavní autori:	Song, Xin, Li, Shuhua, Qi, Ziqiang, Zhu, Jianlin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.05.2023 Springer Nature B.V
Predmet:	Algorithms Artificial Intelligence Clustering Computer Science Datasets Density Euclidean geometry Graph theory Machines Manufacturing Mathematical analysis Mechanical Engineering Processes Density peaks clustering algorithm Histogram clustering algorithm Spectral clustering Attribute fluctuation
ISSN:	0924-669X, 1573-7497
On-line prístup:	Získať plný text
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