Online HDBSCAN
Online HDBSCAN extends the HDBSCAN hierarchical density-based clustering algorithm to incrementally process streaming or sequentially arriving data. Rather than rebuilding the full hierarchy from scratch with each new observation, it maintains and locally updates the mutual reachability graph, minimum spanning tree, condensed cluster tree, and stability-based cluster extraction, enabling continuous density-based clustering without full-dataset reprocessing.
Rekod sumber
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- Hassani, M., Seidl, T. (2017). Using internal evaluation measures to validate the quality of diverse stream clustering algorithms. Vietnam Journal of Computer Science, 4(3), 171–183. · DOI 10.1007/s40595-016-0086-9
- 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
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