# SOME DESCRIPTIVE TITLE.
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# This file is distributed under the same license as the mars package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2020.
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#: ../../source/reference/learn/generated/mars.learn.metrics.pairwise.euclidean_distances.rst:2
msgid "mars.learn.metrics.pairwise.euclidean\\_distances"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:1 of
msgid ""
"Considering the rows of X (and Y=X) as vectors, compute the distance "
"matrix between each pair of vectors."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:4 of
msgid ""
"For efficiency reasons, the euclidean distance between a pair of row "
"vector x and y is computed as::"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:9 of
msgid ""
"This formulation has two advantages over other ways of computing "
"distances. First, it is computationally efficient when dealing with "
"sparse data. Second, if one argument varies but the other remains "
"unchanged, then `dot(x, x)` and/or `dot(y, y)` can be pre-computed."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:14 of
msgid ""
"However, this is not the most precise way of doing this computation, and "
"the distance matrix returned by this function may not be exactly "
"symmetric as required by, e.g., ``scipy.spatial.distance`` functions."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:18 of
msgid "Read more in the :ref:`User Guide <metrics>`."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances of
msgid "Parameters"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:24 of
msgid ""
"Pre-computed dot-products of vectors in Y (e.g., ``(Y**2).sum(axis=1)``) "
"May be ignored in some cases, see the note below."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:28 of
msgid "Return squared Euclidean distances."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:30 of
msgid ""
"Pre-computed dot-products of vectors in X (e.g., ``(X**2).sum(axis=1)``) "
"May be ignored in some cases, see the note below."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:36 of
msgid "Notes"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:37 of
msgid ""
"To achieve better accuracy, `X_norm_squared` and `Y_norm_squared` may be "
"unused if they are passed as ``float32``."
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances of
msgid "Returns"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:40 of
msgid "**distances**"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances of
msgid "Return type"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:44 of
msgid "Examples"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:58 of
msgid ":func:`paired_distances`"
msgstr ""

#: mars.learn.metrics.pairwise.euclidean_distances:59 of
msgid "distances betweens pairs of elements of X and Y."
msgstr ""

