Density Peaks Clustering Algorithm Based on Weighted <italic>k</italic>-Nearest Neighbors and Geodesic Distance

Density Peaks Clustering Algorithm Based on Weighted <italic>k</italic>-Nearest Neighbors and Geodesic Distance

Density peaks clustering (DPC) is a density-based clustering algorithm with excellent clustering performance including accuracy, automatically detecting the number of clusters, and identifying center points. However, DPC has some shortcomings to be addressed before it can be widely applied. For exam...

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Bibliographic Details
Main Authors: Lina Liu, Donghua Yu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Cluster analysis
density peaks clustering
weighted <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k</italic>-nearest neighbors
geodesic distance
Online Access:https://ieeexplore.ieee.org/document/9186660/

Internet

https://ieeexplore.ieee.org/document/9186660/

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