H2OAnomalyMetrics Class¶
The class makes available all metrics that shared across all algorithms supporting anomaly detection.
Getter Methods
- 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
- getMeanNormalizedScore()
Returns: Mean Normalized Anomaly Score.
Scala type:
Double
, Python type:float
, R type:numeric
- getMeanScore()
Returns: Mean Anomaly Score.
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
- 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