HDBSCAN

HDBSCAN is both a Density-based Method and a Hierarchical Clustering Method for Clustering, as it extends DBSCAN algorithm. This algorithm first finds the core distance of each data point, then expands clusters from this density centers.


Advantages:

  • This algorithm has all advantages of DBSCAN:
    • DBSCAN is good at handling Outliers and is robust to noise.
    • it can create arbitrarily shaped clusters(none-linear and oddly shaped data).
    • It can work well even if the shape and number of clusters is unknown.
    • It can cluster items with varying densities.
  • This algorithm is capable of identifying clusters of varying densities.

Disadvantage:

  • It's hard to map unseen objects in HDBSCAN.
  • It's computationally heavy.