8000 MAINT Parameters validation for sklearn.metrics.pairwise.cosine_dista… · scikit-learn/scikit-learn@55f91cc · GitHub
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MAINT Parameters validation for sklearn.metrics.pairwise.cosine_distances (#26046)
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>
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  • sklearn
    • metrics
    • < 8000 svg aria-hidden="true" focusable="false" class="octicon octicon-chevron-down" viewBox="0 0 12 12" width="12" height="12" fill="currentColor" display="inline-block" overflow="visible" style="vertical-align:text-bottom">
      tests

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‎sklearn/metrics/pairwise.py‎

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@@ -980,6 +980,12 @@ def manhattan_distances(X, Y=None, *, sum_over_features="deprecated"):
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return D.reshape((-1, X.shape[1]))
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@validate_params(
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{
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"X": ["array-like", "sparse matrix"],
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"Y": ["array-like", "sparse matrix", None],
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}
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)
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def cosine_distances(X, Y=None):
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"""Compute cosine distance between samples in X and Y.
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‎sklearn/tests/test_public_functions.py‎

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@@ -204,6 +204,7 @@ def _check_function_param_validation(
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"sklearn.metrics.mutual_info_score",
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"sklearn.metrics.ndcg_score",
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"sklearn.metrics.pairwise.additive_chi2_kernel",
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"sklearn.metrics.pairwise.cosine_distances",
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"sklearn.metrics.pairwise.cosine_similarity",
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"sklearn.metrics.pairwise.haversine_distances",
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"sklearn.metrics.pairwise.laplacian_kernel",

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