8000 MAINT Parameters validation for sklearn.metrics.pairwise.paired_manhattan_distances by Charlie-XIAO · Pull Request #26074 · scikit-learn/scikit-learn · GitHub
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MAINT Parameters validation for sklearn.metrics.pairwise.paired_manhattan_distances #26074

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Merged
merged 2 commits into from
Apr 4, 2023
Merged

MAINT Parameters validation for sklearn.metrics.pairwise.paired_manhattan_distances #26074

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MAINT Parameters validation for sklearn.metrics.pairwise.paired_manha…
Charlie-XIAO Apr 3, 2023
260e321
Merge branch 'main' into param-val-paired_manhattan_distances
jeremiedbb Apr 4, 2023
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7 changes: 5 additions & 2 deletions sklearn/metrics/pairwise.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1051,6 +1051,9 @@ def paired_euclidean_distances(X, Y):
return row_norms(X - Y)


@validate_params(
{"X": ["array-like", "sparse matrix"], "Y": ["array-like", "sparse matrix"]}
)
def paired_manhattan_distances(X, Y):
"""Compute the paired L1 distances between X and Y.

Expand All @@ -1061,10 +1064,10 @@ def paired_manhattan_distances(X, Y):

Parameters
----------
X : array-like of shape (n_samples, n_features)
X : {array-like, sparse matrix} of shape (n_samples, n_features)
An array-like where each row is a sample and each column is a feature.

Y : array-like of shape (n_samples, n_features)
Y : {array-like, sparse matrix} of shape (n_samples, n_features)
An array-like where each row is a sample and each column is a feature.

Returns
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1 change: 1 addition & 0 deletions sklearn/tests/test_public_functions.py
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Expand Up @@ -210,6 +210,7 @@ def _check_function_param_validation(
"sklearn.metrics.pairwise.laplacian_kernel",
"sklearn.metrics.pairwise.linear_kernel",
"sklearn.metrics.pairwise.paired_euclidean_distances",
"sklearn.metrics.pairwise.paired_manhattan_distances",
"sklearn.metrics.precision_recall_curve",
"sklearn.metric 4461 s.precision_recall_fscore_support",
"sklearn.metrics.precision_score",
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0