# PerformanceMetrics
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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](https://docs.aws.amazon.com/machine-learning/latest/dg). 

## Contents
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 ** Properties **   <a name="amazonml-Type-PerformanceMetrics-Properties"></a>
Specific performance metric information.  
Type: String to string map  
Required: No

## See Also
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For more information about using this API in one of the language-specific AWS SDKs, see the following:
+  [AWS SDK for C\$1\$1](https://docs.aws.amazon.com/goto/SdkForCpp/machinelearning-2014-12-12/PerformanceMetrics) 
+  [AWS SDK for Java V2](https://docs.aws.amazon.com/goto/SdkForJavaV2/machinelearning-2014-12-12/PerformanceMetrics) 
+  [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/machinelearning-2014-12-12/PerformanceMetrics)