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#: ../../source/reference/learn/generated/mars.learn.metrics.roc_curve.rst:2
msgid "mars.learn.metrics.roc\\_curve"
msgstr ""

#: mars.learn.metrics.roc_curve:1 of
msgid "Compute Receiver operating characteristic (ROC)"
msgstr ""

#: mars.learn.metrics.roc_curve:3 of
msgid "Note: this implementation is restricted to the binary classification task."
msgstr ""

#: mars.learn.metrics.roc_curve:5 of
msgid "Read more in the :ref:`User Guide <roc_metrics>`."
msgstr ""

#: mars.learn.metrics.roc_curve of
msgid "Parameters"
msgstr ""

#: mars.learn.metrics.roc_curve:7 of
msgid ""
"True binary labels. If labels are not either {-1, 1} or {0, 1}, then "
"pos_label should be explicitly given."
msgstr ""

#: mars.learn.metrics.roc_curve:10 of
msgid ""
"Target scores, can either be probability estimates of the positive class,"
" confidence values, or non-thresholded measure of decisions (as returned "
"by \"decision_function\" on some classifiers)."
msgstr ""

#: mars.learn.metrics.roc_curve:14 of
msgid ""
"The label of the positive class. When ``pos_label=None``, if y_true is in"
" {-1, 1} or {0, 1}, ``pos_label`` is set to 1, otherwise an error will be"
" raised."
msgstr ""

#: mars.learn.metrics.roc_curve:18 of
msgid "Sample weights."
msgstr ""

#: mars.learn.metrics.roc_curve:20 of
msgid ""
"Whether to drop some suboptimal thresholds which would not appear on a "
"plotted ROC curve. This is useful in order to create lighter ROC curves."
"  .. versionadded:: 0.17    parameter *drop_intermediate*."
msgstr ""

#: mars.learn.metrics.roc_curve:20 of
msgid ""
"Whether to drop some suboptimal thresholds which would not appear on a "
"plotted ROC curve. This is useful in order to create lighter ROC curves."
msgstr ""

#: mars.learn.metrics.roc_curve:24 of
msgid "parameter *drop_intermediate*."
msgstr ""

#: mars.learn.metrics.roc_curve of
msgid "Returns"
msgstr ""

#: mars.learn.metrics.roc_curve:28 of
msgid ""
"* **fpr** (*tensor, shape = [>2]*) -- Increasing false positive rates "
"such that element i is the false   positive rate of predictions with "
"score >= thresholds[i]. * **tpr** (*tensor, shape = [>2]*) -- Increasing "
"true positive rates such that element i is the true   positive rate of "
"predictions with score >= thresholds[i]. * **thresholds** (*tensor, shape"
" = [n_thresholds]*) -- Decreasing thresholds on the decision function "
"used to compute   fpr and tpr. `thresholds[0]` represents no instances "
"being predicted   and is arbitrarily set to `max(y_score) + 1`."
msgstr ""

#: mars.learn.metrics.roc_curve:28 of
msgid ""
"**fpr** (*tensor, shape = [>2]*) -- Increasing false positive rates such "
"that element i is the false positive rate of predictions with score >= "
"thresholds[i]."
msgstr ""

#: mars.learn.metrics.roc_curve:30 of
msgid ""
"**tpr** (*tensor, shape = [>2]*) -- Increasing true positive rates such "
"that element i is the true positive rate of predictions with score >= "
"thresholds[i]."
msgstr ""

#: mars.learn.metrics.roc_curve:32 of
msgid ""
"**thresholds** (*tensor, shape = [n_thresholds]*) -- Decreasing "
"thresholds on the decision function used to compute fpr and tpr. "
"`thresholds[0]` represents no instances being predicted and is "
"arbitrarily set to `max(y_score) + 1`."
msgstr ""

#: mars.learn.metrics.roc_curve:38 of
msgid ":func:`roc_auc_score`"
msgstr ""

#: mars.learn.metrics.roc_curve:39 of
msgid "Compute the area under the ROC curve"
msgstr ""

#: mars.learn.metrics.roc_curve:42 of
msgid "Notes"
msgstr ""

#: mars.learn.metrics.roc_curve:43 of
msgid ""
"Since the thresholds are sorted from low to high values, they are "
"reversed upon returning them to ensure they correspond to both ``fpr`` "
"and ``tpr``, which are sorted in reversed order during their calculation."
msgstr ""

#: mars.learn.metrics.roc_curve:48 of
msgid "References"
msgstr ""

#: mars.learn.metrics.roc_curve:49 of
msgid ""
"`Wikipedia entry for the Receiver operating characteristic "
"<https://en.wikipedia.org/wiki/Receiver_operating_characteristic>`_"
msgstr ""

#: mars.learn.metrics.roc_curve:52 of
msgid ""
"Fawcett T. An introduction to ROC analysis[J]. Pattern Recognition "
"Letters, 2006, 27(8):861-874."
msgstr ""

#: mars.learn.metrics.roc_curve:56 of
msgid "Examples"
msgstr ""

