Accelerated Hierarchical Density Based Clustering

@article{McInnes2017AcceleratedHD,
  title={Accelerated Hierarchical Density Based Clustering},
  author={Leland McInnes and John Healy},
  journal={2017 IEEE International Conference on Data Mining Workshops (ICDMW)},
  year={2017},
  pages={33-42}
}
  • Leland McInnes, John Healy
  • Published in
    IEEE International Conference…
    2017
  • Mathematics, Computer Science
  • 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… CONTINUE READING

    Figures and Topics from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 35 CITATIONS

    Anomaly-based detection of lateral movement in a Microsoft Windows environment

    VIEW 4 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    FISHDBC: Flexible, Incremental, Scalable, Hierarchical Density-Based Clustering for Arbitrary Data and Distance

    VIEW 8 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Genetic Programming Theory and Practice XVI

    VIEW 5 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Stable components and layers

    VIEW 4 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    A flexible EM-like clustering algorithm for noisy data

    VIEW 6 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    Reference-Free Measurement of the Classification Reliability of Vector-Based Land Cover Mapping

    VIEW 3 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    Ensemble Learning for Load Forecasting

    VIEW 1 EXCERPT

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 60 REFERENCES

    hdbscan: Hierarchical density based clustering

    VIEW 9 EXCERPTS

    Estimating the Cluster Tree of a Density by Analyzing the Minimal Spanning Tree of a Sample

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    The estimation of the gradient of a density function, with applications in pattern recognition

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    What are the true clusters?

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    Estimation of a convex density contour in two dimensions

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Consistency of Single Linkage for High-Density Clusters

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    A Density-Sensitive Hierarchical Clustering Method

    VIEW 1 EXCERPT

    Persistent density clustering

    • J. Healy, L. McInnes
    • Forthcoming
    • 2017
    VIEW 2 EXCERPTS