index.rst

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
   dbscan_from_hdbscan
   how_to_detect_branches
   faq

Background on Clustering with HDBSCAN

.. toctree::
   :maxdepth: 2

   how_hdbscan_works
   comparing_clustering_algorithms
   performance_and_scalability
   soft_clustering_explanation

API Reference

.. toctree::

   api

Indices and tables

• :ref:`genindex`
• :ref:`modindex`
• :ref:`search`