HDBSCAN
HDBSCAN (Hierarchical Density-Based Spatial Clustering of Applications with Noise) je algoritam klasterovanja zasnovan na gustini koji su uveli Kampello, Moulavi i Sander 2013. godine. On proširuje DBSCAN algoritamsku proceduru gradeći punu hijerarhiju klastera zasnovanih na gustini preko svih skala gustine, a zatim izdvajajući stabilnu ravnu particiju, čime postaje otporan na skupove podataka gde se gustine klastera značajno razlikuju u različitim regionima.
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Izvori
- Campello, R. J. G. B., Moulavi, D., & Sander, J. (2013). Density-Based Clustering Based on Hierarchical Density Estimates. In J. Pei et al. (Eds.), Advances in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science, vol. 7819 (pp. 160–172). Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-37456-2_14 ↗
- Campello, R. J. G. B., Moulavi, D., Zimek, A., & Sander, J. (2015). Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection. ACM Transactions on Knowledge Discovery from Data, 10(1), Article 5. DOI: 10.1145/2733381 ↗
- McInnes, L., Healy, J., & Astels, S. (2017). hdbscan: Hierarchical density based clustering. Journal of Open Source Software, 2(11), 205. DOI: 10.21105/joss.00205 ↗
Kako citirati ovu stranicu
ScholarGate. (2026, June 3). Hierarchical Density-Based Spatial Clustering of Applications with Noise. ScholarGate. https://scholargate.app/sr/machine-learning/hdbscan
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- DBSCANMašinsko učenje↔ compare
- OPTICSMašinsko učenje↔ compare
- Спектрално груписањеMašinsko učenje↔ compare
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