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DOC Fix typo in parameter description of KMeans #25649

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Feb 20, 2023
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DOC Fix typo in parameter description of KMeans #25649

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2 changes: 1 addition & 1 deletion examples/cluster/plot_kmeans_digits.py
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Expand Up @@ -114,7 +114,7 @@ def bench_k_means(kmeans, name, data, labels):
#
# We will compare three approaches:
#
# * an initialization using `kmeans++`. This method is stochastic and we will
# * an initialization using `k-means++`. This method is stochastic and we will
# run the initialization 4 times;
# * a random initialization. This method is stochastic as well and we will run
# the initialization 4 times;
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2 changes: 1 addition & 1 deletion examples/cluster/plot_kmeans_plusplus.py
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Expand Up @@ -23,7 +23,7 @@
)
X = X[:, ::-1]

# Calculate seeds from kmeans++
# Calculate seeds from k-means++
centers_init, indices = kmeans_plusplus(X, n_clusters=4, random_state=0)

# Plot init seeds along side sample data
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2 changes: 1 addition & 1 deletion examples/cluster/plot_kmeans_stability_low_dim_dense.py
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Expand Up @@ -10,7 +10,7 @@

The first plot shows the best inertia reached for each combination
of the model (``KMeans`` or ``MiniBatchKMeans``), and the init method
(``init="random"`` or ``init="kmeans++"``) for increasing values of the
(``init="random"`` or ``init="k-means++"``) for increasing values of the
``n_init`` parameter that controls the number of initializations.

The second plot demonstrates one single run of the ``MiniBatchKMeans``
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6 changes: 3 additions & 3 deletions sklearn/cluster/_kmeans.py
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Expand Up @@ -345,7 +345,7 @@ def k_means(
n_init consecutive runs in terms of inertia.

When `n_init='auto'`, the number of runs depends on the value of init:
10 if using `init='random'`, 1 if using `init='kmeans++'`.
10 if using `init='random'`, 1 if using `init='k-means++'`.

.. versionadded:: 1.2
Added 'auto' option for `n_init`.
Expand Down Expand Up @@ -1206,7 +1206,7 @@ class KMeans(_BaseKMeans):
high-dimensional problems (see :ref:`kmeans_sparse_high_dim`).

When `n_init='auto'`, the number of runs depends on the value of init:
10 if using `init='random'`, 1 if using `init='kmeans++'`.
10 if using `init='random'`, 1 if using `init='k-means++'`.

.. versionadded:: 1.2
Added 'auto' option for `n_init`.
Expand Down Expand Up @@ -1734,7 +1734,7 @@ class MiniBatchKMeans(_BaseKMeans):
:ref:`kmeans_sparse_high_dim`).

When `n_init='auto'`, the number of runs depends on the value of init:
3 if using `init='random'`, 1 if using `init='kmeans++'`.
3 if using `init='random'`, 1 if using `init='k-means++'`.

.. versionadded:: 1.2
Added 'auto' option for `n_init`.
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