8000 MAINT Parameters validation for sklearn.metrics.pairwise.paired_eucli… · scikit-learn/scikit-learn@1a9f5eb · GitHub
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MAINT Parameters validation for sklearn.metrics.pairwise.paired_euclidean_distances (#26073)
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‎sklearn/metrics/pairwise.py‎

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@@ -1025,17 +1025,20 @@ def cosine_distances(X, Y=None):
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# Paired distances
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@validate_params(
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{"X": ["array-like", "sparse matrix"], "Y": ["array-like", "sparse matrix"]}
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)
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def paired_euclidean_distances(X, Y):
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"""Compute the paired euclidean distances between X and Y.
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Read more in the :ref:`User Guide <metrics>`.
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Parameters
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----------
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X : array-like of shape (n_samples, n_features)
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X : {array-like, sparse matrix} of shape (n_samples, n_features)
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Input array/matrix X.
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Y : array-like of shape (n_samples, n_features)
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Y : {array-like, sparse matrix} of shape (n_samples, n_features)
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Input array/matrix Y.
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Returns

‎sklearn/tests/test_public_functions.py‎

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@@ -209,6 +209,7 @@ def _check_function_param_validation(
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"sklearn.metrics.pairwise.haversine_distances",
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"sklearn.metrics.pairwise.laplacian_kernel",
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"sklearn.metrics.pairwise.linear_kernel",
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"sklearn.metrics.pairwise.paired_euclidean_distances",
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"sklearn.metrics.precision_recall_curve",
< 430B /td>
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"sklearn.metrics.precision_recall_fscore_support",
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"sklearn.metrics.precision_score",

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