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k-means++ documented as a init option #7615

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rapids-bot merged 2 commits into from
Dec 17, 2025
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k-means++ documented as a init option #7615

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aamijar Dec 16, 2025
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aamijar Dec 16, 2025
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7 changes: 4 additions & 3 deletions python/cuml/cuml/cluster/kmeans.pyx
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Expand Up @@ -322,11 +322,12 @@ class KMeans(Base,
random_state : int or None (default = None)
If you want results to be the same when you restart Python, select a
state.
init : {'scalable-k-means++', 'k-means||', 'random'} or an \
init : {'scalable-k-means++', 'k-means||', 'k-means++', 'random'} or an \
ndarray (default = 'scalable-k-means++')

- ``'scalable-k-means++'`` or ``'k-means||'``: Uses fast and stable
scalable kmeans++ initialization.
scalable kmeans++ initialization. k-means++ is the constrained case of k-means||
with `oversampling_factor=0`
- ``'random'``: Choose `n_cluster` observations (rows) at random
from data for the initial centroids.
- If an ndarray is passed, it should be of
Expand Down Expand Up @@ -422,7 +423,7 @@ class KMeans(Base,
raise UnsupportedOnGPU(f"`init={model.init!r}` is not supported")
elif isinstance(model.init, str):
if model.init == "k-means++":
init = "scalable-k-means++"
init = "k-means++"
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elif model.init == "random":
init = "random"
else:
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