Density peaks clustering using geodesic distances
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-017-0648-x
Abstract: Density peaks clustering (DPC) algorithm is a novel clustering algorithm based on density. It needs neither iterative process nor more parameters. However, it cannot effectively group data with arbitrary shapes, or multi-manifold structures. To handle… read more here.
Keywords: using geodesic; density; peaks clustering; geodesic distances ... See more keywords
Fast density-peaks clustering for registration-free pediatric white matter tract analysis
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DOI: 10.1016/j.artmed.2019.03.002
Abstract: Clustering white matter (WM) tracts from diffusion tensor imaging (DTI) is primarily important for quantitative analysis on pediatric brain development. A recently developed algorithm, density peaks (DP) clustering, demonstrates great robustness to the complex structural… read more here.
Keywords: density peaks; density; peaks clustering; analysis ... See more keywords
DPC-LG: Density peaks clustering based on logistic distribution and gravitation
Sign Up to like & getrecommendations! Published in 2019 at "Physica A: Statistical Mechanics and its Applications"
DOI: 10.1016/j.physa.2018.09.002
Abstract: The Density Peaks Clustering (DPC) algorithm, published in Science, is a novel density-based clustering approach. Gravitation-based Density Peaks Clustering (GDPC) algorithm, inherited the advantages of DPC, is an improved algorithm. GDPC is able to detect… read more here.
Keywords: dpc; density peaks; gravitation; density ... See more keywords
Differential Privacy-Preserving Density Peaks Clustering Based on Shared Near Neighbors Similarity
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DOI: 10.1109/access.2019.2927308
Abstract: Density peaks clustering is a novel and efficient density-based clustering algorithm. However, the problem of the sensitive information leakage and the associated security risk with the applications of clustering methods is rarely considered. To address… read more here.
Keywords: density peaks; density; shared near; near neighbors ... See more keywords
Effective Density Peaks Clustering Algorithm Based on the Layered K-Nearest Neighbors and Subcluster Merging
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DOI: 10.1109/access.2020.3006069
Abstract: Density peaks clustering (DPC) algorithm is a novel density-based clustering algorithm, which is simple and efficient, is not necessary to specify the number of clusters in advance, and can find any nonspherical class clusters. However,… read more here.
Keywords: density peaks; clustering algorithm; density; nearest neighbors ... See more keywords
A Density Peaks Clustering Algorithm With Sparse Search and K-d Tree
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DOI: 10.1109/access.2022.3190958
Abstract: Density peaks clustering has become a nova of clustering algorithm because of its simplicity and practicality. However, there is one main drawback: it is time-consuming due to its high computational complexity. Herein, a density peaks… read more here.
Keywords: density peaks; density; peaks clustering; tex math ... See more keywords
Density Peaks Clustering Based on Potential Model and Diffusion Strength
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3227936
Abstract: Density peaks clustering (DPC) is a simple and efficient density-based clustering algorithm without complex iterative procedures. However, DPC needs to manually choose clustering centers via a decision graph, which often can’t identify real centers and… read more here.
Keywords: density peaks; diffusion; density; peaks clustering ... See more keywords