.. _metrics_H2OBinomialMetrics:

H2OBinomialMetrics Class
------------------------

The class makes available all metrics that shared across all algorithms supporting binomial classification.

**Getter Methods**

getAUC()
  **Returns:** The AUC for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getConfusionMatrix()
  **Returns:** The ConfusionMatrix at the threshold for maximum F1.

  *Type:* ``DataFrame``

getCustomMetricName()
  **Returns:** Name of custom metric.

  *Scala type:* ``String``, *Python type:* ``string``, *R type:* ``character``

getCustomMetricValue()
  **Returns:** Value of custom metric.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getDataFrameSerializer()
  **Returns:** A full name of a serializer used for serialization and deserialization of Spark DataFrames to a JSON value within NullableDataFrameParam.

  *Scala type:* ``String``, *Python type:* ``string``, *R type:* ``character``

getDescription()
  **Returns:** Optional description for this scoring run (to note out-of-bag, sampled data, etc.).

  *Scala type:* ``String``, *Python type:* ``string``, *R type:* ``character``

getGainsLiftTable()
  **Returns:** Gains and Lift table.

  *Type:* ``DataFrame``

getGini()
  **Returns:** The Gini score for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getLogloss()
  **Returns:** The logarithmic loss for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getMaxCriteriaAndMetricScores()
  **Returns:** The Metrics for various criteria.

  *Type:* ``DataFrame``

getMeanPerClassError()
  **Returns:** The mean misclassification error per class.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getMSE()
  **Returns:** The Mean Squared Error of the prediction for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getNobs()
  **Returns:** Number of observations.

  *Scala type:* ``Long``, *Python type:* ``int``, *R type:* ``integer``

getPRAUC()
  **Returns:** The precision-recall AUC for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getR2()
  **Returns:** The R^2 for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getRMSE()
  **Returns:** The Root Mean Squared Error of the prediction for this scoring run.

  *Scala type:* ``Double``, *Python type:* ``float``, *R type:* ``numeric``

getScoringTime()
  **Returns:** The time in mS since the epoch for the start of this scoring run.

  *Scala type:* ``Long``, *Python type:* ``int``, *R type:* ``integer``

getThresholdsAndMetricScores()
  **Returns:** The Metrics for various thresholds.

  *Type:* ``DataFrame``