DEDIC: Density Estimation Clustering Method Using Directly Interconnected Cores

DEDIC: Density Estimation Clustering Method Using Directly Interconnected Cores

Numerous clustering algorithms become invalid when data classes are unbalanced and close to each other, or clusters are arbitrary shapes and have different densities. A novel region density based clustering algorithm, DEDIC, is proposed to meet this challenge. It is based on recognizing dense region...

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Detalles Bibliográficos
Autores principales: Yisen Lin, Xinlun Zhang, Lei Liu, Huichen Qu
Formato: Artículo
Lenguaje:English
Publicado: IEEE 2022-01-01
Colección:IEEE Access
Materias:
Clustering
region density
mutual neighbors
dimensionality reduction
arbitrary shapes
pattern recognition
Acceso en línea:https://ieeexplore.ieee.org/document/9987490/

Internet

https://ieeexplore.ieee.org/document/9987490/

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