.. _`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.



**Documentation**

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

*Configuration*:


  - *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.


  - *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*

    Use header of Y-prob as the target label



*Attributes*:




*Input ports*:
    **Y-prob** : table
        Y-prob
    **Y-true** : table
        Y-true

*Output ports*:
    **roc** : table
        roc


**Definition**


*Input ports*

    :Y-prob:  table

        Y-prob

    :Y-true:  table

        Y-true


*Output ports*

    :roc:  table

        roc





.. automodule:: node_metrics

.. class:: ROCFromProb