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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Bibliographic Details
Main Authors:	Yisen Lin, Xinlun Zhang, Lei Liu, Huichen Qu
Format:	Article
Language:	English
Published:	IEEE 2022-01-01
Series:	IEEE Access
Subjects:	Clustering region density mutual neighbors dimensionality reduction arbitrary shapes pattern recognition
Online Access:	https://ieeexplore.ieee.org/document/9987490/

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