Accelerated Hierarchical Density Clustering
This provides an incremental improvement for users of density-based clustering algorithms by making accelerated HDBSCAN* a more efficient and practical default choice.
The paper tackles the problem of improving hierarchical density-based clustering by accelerating HDBSCAN*, achieving comparable performance to DBSCAN while supporting variable density clusters and eliminating the need for a difficult-to-tune distance scale parameter.
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. This makes accelerated HDBSCAN* the default choice for density based clustering. Library available at: https://github.com/scikit-learn-contrib/hdbscan