Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets

Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for exploratory clustering applications. Despite the DBSCAN algorithm being considered an unsupervised pattern recognition method, it has two parameters that must be tuned prior to the clustering process...

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Bibliographic Details
Main Authors: Juan Carlos Perafan-Lopez, Valeria Lucía Ferrer-Gregory, César Nieto-Londoño, Julián Sierra-Pérez
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Entropy
Subjects:
clustering
DBSCAN
factor analysis
genetic algorithm
pattern recognition
entropy
Online Access:https://www.mdpi.com/1099-4300/24/7/875

Internet

https://www.mdpi.com/1099-4300/24/7/875

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