The hdbscan Clustering Library
The hdbscan library is a suite of tools to use unsupervised learning to find clusters, or dense regions, of a dataset. The primary algorithm is HDBSCAN* as proposed by Campello, Moulavi, and Sander. The library provides a high performance implementation of this algorithm, along with tools for analysing the resulting clustering.
User Guide / Tutorial
.. toctree:: :maxdepth: 2 basic_hdbscan advanced_hdbscan parameter_selection outlier_detection prediction_tutorial soft_clustering how_to_use_epsilon faq
Background on Clustering with HDBSCAN
.. toctree:: :maxdepth: 2 how_hdbscan_works comparing_clustering_algorithms performance_and_scalability soft_clustering_explanation
.. toctree:: api