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DOC Added information about space complexity to docs DBSCAN #26783

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Merged
merged 4 commits into from
Jul 20, 2023
Merged

DOC Added information about space complexity to docs DBSCAN #26783

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365dca2
Doc extended with info about space complexity
StefanieSenger Jul 6, 2023
cbe4b38
formatting
StefanieSenger Jul 6, 2023
0b4004f
added clarification for param description 'min_samples'
StefanieSenger Jul 7, 2023
d200e03
Update sklearn/cluster/_dbscan.py
StefanieSenger Jul 13, 2023
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10 changes: 8 additions & 2 deletions sklearn/cluster/_dbscan.py
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Expand Up @@ -172,6 +172,9 @@ class DBSCAN(ClusterMixin, BaseEstimator):
Finds core samples of high density and expands clusters from them.
Good for data which contains clusters of similar density.

The worst case memory complexity of DBSCAN is :math:`O({n}^2)`, which can
occur when the `eps` param is large and `min_samples` is low.

Read more in the :ref:`User Guide <dbscan>`.

Parameters
Expand All @@ -184,8 +187,11 @@ class DBSCAN(ClusterMixin, BaseEstimator):
and distance function.

min_samples : int, default=5
The number of samples (or total weight) in a neighborhood for a point
to be considered as a core point. This includes the point itself.
The number of samples (or total weight) in a neighborhood for a point to
be considered as a core point. This includes the point itself. If
`min_samples` is set to a higher value, DBSCAN will find denser clusters,
whereas if it is set to a lower value, the found clusters will be more
sparse.

metric : str, or callable, default='euclidean'
The metric to use when calculating distance between instances in a
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