HDBSCAN
HDBSCANA model type for constructing a hdbscan, based on MLJScikitLearnInterface.jl, and implementing the MLJ model interface.
From MLJ, the type can be imported using
HDBSCAN = @load HDBSCAN pkg=MLJScikitLearnInterfaceDo model = HDBSCAN() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in HDBSCAN(min_cluster_size=...).
Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection.