Class PerformanceMetrics
java.lang.Object
com.amazonaws.services.machinelearning.model.PerformanceMetrics
- All Implemented Interfaces:
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.
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionaddPropertiesEntry
(String key, String value) Removes all the entries added into Properties.clone()
boolean
int
hashCode()
void
setProperties
(Map<String, String> properties) toString()
Returns a string representation of this object; useful for testing and debugging.withProperties
(Map<String, String> properties)
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Constructor Details
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PerformanceMetrics
public PerformanceMetrics()
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Method Details
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getProperties
- Returns:
-
setProperties
- Parameters:
properties
-
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withProperties
- Parameters:
properties
-- Returns:
- Returns a reference to this object so that method calls can be chained together.
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addPropertiesEntry
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clearPropertiesEntries
Removes all the entries added into Properties. <p> Returns a reference to this object so that method calls can be chained together. -
toString
Returns a string representation of this object; useful for testing and debugging. -
equals
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hashCode
public int hashCode() -
clone
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