Density peaks clustering based on k-nearest neighbors and self-recommendation
Density peaks clustering based on k-nearest neighbors and self-recommendation
About this item
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Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
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Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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Scope and Contents
Contents
Density peaks clustering (DPC) model focuses on searching density peaks and clustering data with arbitrary shapes for machine learning. However, it is difficult for DPC to select a cut-off distance in the calculation of a local density of points, and DPC easily ignores the cluster centers with lower density in datasets with variable densities. In a...
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Full title
Density peaks clustering based on k-nearest neighbors and self-recommendation
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Author / Creator
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Record Identifier
TN_cdi_proquest_journals_2920285366
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2920285366
Other Identifiers
ISSN
1868-8071
E-ISSN
1868-808X
DOI
10.1007/s13042-021-01284-x
