Accelerated Hierarchical Density Based Clustering

Leland McInnes, John Healy
2017
2 references

Abstract

We present an accelerated algorithm for hierarchical density based clustering. Our new algorithm improves upon HDBSCAN*, which itself provided a significant qualitative improvement over the popular DBSCAN algorithm. The accelerated HDBSCAN* algorithm provides comparable performance to DBSCAN, while supporting variable density clusters, and eliminating the need for the difficult to tune distance scale parameter epsilon. This makes accelerated HDBSCAN* the default choice for density based clustering.

1 repository
2 references

Code References

â–¶ scikit-learn/scikit-learn
1 file
â–¶ doc/modules/clustering.rst
2
`scikit-learn-contrib/hdbscan <https://github.com/scikit-learn-contrib/hdbscan>`_ based on [LJ2017]_.
.. [LJ2017] L. McInnes and J. Healy, (2017). Accelerated Hierarchical Density
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