H2OOrdinalMetrics Class

The class makes available all metrics that shared across all algorithms supporting ordinal regression.

Getter Methods

getConfusionMatrix()

Returns: The ConfusionMatrix object for this scoring run.

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

getHitRatioTable()

Returns: The hit ratio table for this scoring run.

Type: DataFrame

getLogloss()

Returns: The logarithmic loss for this scoring run.

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

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

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