.. _`ROC from Probabilities`:

.. _`org.sysess.sympathy.machinelearning.roc_prob`:

ROC from Probabilities
``````````````````````

.. image:: roc_curve.svg
   :width: 48


Computes Receiver operating characteristics (ROC) based on calculated Y-probabilities and from true Y.





Definition
::::::::::


Input ports
...........

    **Y-prob**  table
        Y-prob

    **Y-true**  table
        Y-true


Output ports
............

    **roc**  table
        roc




Configuration
.............

    **Drop suboptimal thresholds** (drop_intermediate)
        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*.
    **header as label** (header as label)
        Use header of Y-prob as the target label
    **Positive class label** (pos_label)
        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.









Implementation
..............

.. automodule:: node_metrics
    :noindex:

.. class:: ROCFromProb
    :noindex: