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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.
Namespace: Amazon.MachineLearning.Model
Assembly: AWSSDK.MachineLearning.dll
Version: 3.x.y.z
public class PerformanceMetrics
The PerformanceMetrics type exposes the following members
Name | Description | |
---|---|---|
PerformanceMetrics() |
Name | Type | Description | |
---|---|---|---|
Properties | System.Collections.Generic.Dictionary<System.String, System.String> |
Gets and sets the property Properties. |
.NET Core App:
Supported in: 3.1
.NET Standard:
Supported in: 2.0
.NET Framework:
Supported in: 4.5, 4.0, 3.5