Comparative Analysis Review of Pioneering DBSCAN and Successive Density-Based Clustering Algorithms

Comparative Analysis Review of Pioneering DBSCAN and Successive Density-Based Clustering Algorithms

The density-based spatial clustering of applications with noise (DBSCAN) is regarded as a pioneering algorithm of the density-based clustering technique. It provides the ability to handle outlier objects, detect clusters of different shapes, and disregard the need for prior knowledge about existing...

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Bibliographic Details
Main Authors: Adil Abdu Bushra, Gangman Yi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Unsupervised learning
clustering
DBSCAN
spatial database
Online Access:https://ieeexplore.ieee.org/document/9453785/

Internet

https://ieeexplore.ieee.org/document/9453785/

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