COMPARISON OF DATA CLUSTERING ALGORITHMS
DOI:
https://doi.org/10.30888/2709-2267.2024-22-00-028Keywords:
data clustering, cluster analysis, K-Means, Hierarchical Agglomerative Clustering (HAC), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Expectation–Maximization clustering using Gaussian Mixture Models (GMM).Abstract
The article compares the comparison of data clustering algorithms: K-Means, Hierarchical Agglomerative Clustering (HAC), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Expectation–Maximization clustering using Gaussian Mixture ModelMetrics
Metrics Loading ...
References
Simulations, Of & Zaidi, Habib & Labb, Claire & Morel, Christian. (1999). Improvement of the performance and accuracy of PET Monte Carlo simulations. Proc. SPIE. 3659. 10.1117/12.349537
Doroshenko I.V., Knihnitska T.V., Deretorska T.I. Comparison of machine learning algorithms for predicting mortality from Covid-19 virus // Sworld Jornal Issue No11, Part 2 January 2022 – P. 72-77 (https://www.sworldjournal.com/index.php/swj/article/view/swj11-02-045).
Downloads
Published
2024-01-30
How to Cite
Doroshenko, I., Knihnitska, T., & Kreshtanovych, M. (2024). COMPARISON OF DATA CLUSTERING ALGORITHMS. Sworld-Us Conference Proceedings, 1(usc22-01), 32–38. https://doi.org/10.30888/2709-2267.2024-22-00-028
Issue
Section
Abstracts
License
Copyright (c) 2024 Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
