public class PerformanceMetrics extends Object implements Serializable, Cloneable
Measurements of how well the MLModel
performed on known observations. One of the following metrics is
returned, based on the type of the MLModel
:
BinaryAUC: The binary MLModel
uses the Area Under the Curve (AUC) technique to measure performance.
RegressionRMSE: The regression MLModel
uses the Root Mean Square Error (RMSE) technique to measure
performance. RMSE measures the difference between predicted and actual values for a single variable.
MulticlassAvgFScore: The multiclass MLModel
uses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
Constructor and Description |
---|
PerformanceMetrics() |
Modifier and Type | Method and Description |
---|---|
PerformanceMetrics |
addPropertiesEntry(String key,
String value) |
PerformanceMetrics |
clearPropertiesEntries()
Removes all the entries added into Properties.
|
PerformanceMetrics |
clone() |
boolean |
equals(Object obj) |
Map<String,String> |
getProperties() |
int |
hashCode() |
void |
setProperties(Map<String,String> properties) |
String |
toString()
Returns a string representation of this object; useful for testing and debugging.
|
PerformanceMetrics |
withProperties(Map<String,String> properties) |
public PerformanceMetrics withProperties(Map<String,String> properties)
properties
- public PerformanceMetrics addPropertiesEntry(String key, String value)
public PerformanceMetrics clearPropertiesEntries()
public String toString()
toString
in class Object
Object.toString()
public PerformanceMetrics clone()
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