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FIX ‘sparse’ kwarg was not used by fowlkes_mallows_score #28981

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FIX ‘sparse’ kwarg was not used by fowlkes_mallows_score #28981

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6 changes: 3 additions & 3 deletions sklearn/metrics/cluster/_supervised.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1181,7 +1181,7 @@ def normalized_mutual_info_score(
},
prefer_skip_nested_validation=True,
)
def fowlkes_mallows_score(labels_true, labels_pred, *, sparse=False):
def fowlkes_mallows_score(labels_true, labels_pred, *, sparse=True):
"""Measure the similarity of two clusterings of a set of points.

.. versionadded:: 0.18
Expand Down Expand Up @@ -1212,7 +1212,7 @@ def fowlkes_mallows_score(labels_true, labels_pred, *, sparse=False):
labels_pred : array-like of shape (n_samples,), dtype=int
A clustering of the data into disjoint subsets.

sparse : bool, default=False
sparse : bool, default=True
Compute contingency matrix internally with sparse matrix.

Returns
Expand Down Expand Up @@ -1251,7 +1251,7 @@ def fowlkes_mallows_score(labels_true, labels_pred, *, sparse=False):
labels_true, labels_pred = check_clusterings(labels_true, labels_pred)
(n_samples,) = labels_true.shape

c = contingency_matrix(labels_true, labels_pred, sparse=True)
c = contingency_matrix(labels_true, labels_pred, sparse=sparse)
c = c.astype(np.int64, copy=False)
tk = np.dot(c.data, c.data) - n_samples
pk = np.sum(np.asarray(c.sum(axis=0)).ravel() ** 2) - n_samples
Expand Down
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