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Clarify HDBSCAN min_samples semantics #8567

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rapids-bot merged 3 commits into from
Sep 11, 2026
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Clarify HDBSCAN min_samples semantics #8567

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47921b1
Clarify HDBSCAN min_samples semantics
viclafargue Sep 8, 2026
dbae618
Clarify HDBSCAN min_samples conversion boundary
csadorf Sep 10, 2026
18ca64b
Merge branch 'release/26.10' into hdbscan-doc-min-samples-fix
jcrist Sep 11, 2026
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12 changes: 9 additions & 3 deletions python/cuml/cuml/cluster/hdbscan/hdbscan.pyx
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Expand Up @@ -528,9 +528,15 @@ class HDBSCAN(InteropMixin, ClusterMixin, CMajorInputTagMixin, Base):
as noise. Must be greater than one.

min_samples : int, optional (default=None)
The number of samples in a neighborhood for a point
to be considered as a core point. This includes the point itself.
If 'None', it defaults to the min_cluster_size.
The number of nearest neighbors, excluding the point itself, used to
determine a point's core distance. This follows the effective
convention implemented by ``hdbscan.HDBSCAN`` from
scikit-learn-contrib. It differs from
``sklearn.cluster.HDBSCAN``, where ``min_samples`` includes the point
itself. For ``k >= 2``, to match
``sklearn.cluster.HDBSCAN(min_samples=k)``, use
``cuml.cluster.HDBSCAN(min_samples=k - 1)``. The ``k = 1`` case is not
supported by cuML. If 'None', it defaults to the min_cluster_size.
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cluster_selection_epsilon : float, optional (default=0.0)
A distance threshold. Clusters below this value will be merged.
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