.. _`R² regression score (R2)`:

.. _`org.sysess.sympathy.machinelearning.r2_score`:

R² regression score (R2)
~~~~~~~~~~~~~~~~~~~~~~~~

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


Computes the R² regression score.
Best possible score is 1.0 and it can be negative (because the model can be arbitrarily bad). A constant model that always predicts the expected value of y, disregarding the input features, would get a R² score of 0.0)

:Configuration:




:Attributes:




:Inputs:
    **Y-prob** : table
        Y-prob
    **Y-true** : table
        Y-true

:Outputs:
    **r2 score** : table
        r2 score

*Ports*:

    **Inputs**:

        :Y-prob: table

            Y-prob
        :Y-true: table

            Y-true

    **Outputs**:

        :r2 score: table

            r2 score

*Configuration*:



.. automodule:: node_metrics

.. class:: R2Score