Density peaks clustering algorithm with connected local density and punished relative distance
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-023-05688-0.pdf
Reference68 articles.
1. Flores KG, Garza SE (2020) Density peaks clustering with gap-based automatic center detection. Knowl-Based Syst. https://doi.org/10.1016/j.knosys.2020.106350. (in English)
2. Pujari AK, Rajesh K, Reddy DS (2021) Clustering techniques in data mining—a survey. Iete J Res 47(1–2):19–28. https://doi.org/10.1080/03772063.2001.11416199. (in English)
3. Pastuchova E, Vaclavikova S (2013) Cluster analysis—data mining technique for discovering natural groupings in the data. J Electr Eng-Slovak 64(2):128–131. https://doi.org/10.2478/jee-2013-0019. (in English)
4. Gao K, Khan HA, Qu WW (2022) Clustering with missing features: a density-based approach. Symmetry-Basel. https://doi.org/10.3390/sym14010060. (in English)
5. Liu HF, Li J, Wu Y, Fu Y (2021) Clustering with outlier removal. IEEE Trans Knowl Data Eng 33(6):2369–2379. https://doi.org/10.1109/Tkde.2019.2954317. (in English)
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