@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class TrainingResultV2 extends Object implements Serializable, Cloneable, StructuredPojo
The training result details.
| Constructor and Description |
|---|
TrainingResultV2() |
public void setDataValidationMetrics(DataValidationMetrics dataValidationMetrics)
dataValidationMetrics - public DataValidationMetrics getDataValidationMetrics()
public TrainingResultV2 withDataValidationMetrics(DataValidationMetrics dataValidationMetrics)
dataValidationMetrics - public void setTrainingMetricsV2(TrainingMetricsV2 trainingMetricsV2)
The training metric details.
trainingMetricsV2 - The training metric details.public TrainingMetricsV2 getTrainingMetricsV2()
The training metric details.
public TrainingResultV2 withTrainingMetricsV2(TrainingMetricsV2 trainingMetricsV2)
The training metric details.
trainingMetricsV2 - The training metric details.public void setVariableImportanceMetrics(VariableImportanceMetrics variableImportanceMetrics)
variableImportanceMetrics - public VariableImportanceMetrics getVariableImportanceMetrics()
public TrainingResultV2 withVariableImportanceMetrics(VariableImportanceMetrics variableImportanceMetrics)
variableImportanceMetrics - public void setAggregatedVariablesImportanceMetrics(AggregatedVariablesImportanceMetrics aggregatedVariablesImportanceMetrics)
The variable importance metrics of the aggregated variables.
Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
calculate the number of times an user has logged in using the same IP address. In this case, event variables used
to derive the aggregated variables are IP address and user.
aggregatedVariablesImportanceMetrics - The variable importance metrics of the aggregated variables.
Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
calculate a set of variables (aggregated variables) based on historical events. For example, your ATI
model might calculate the number of times an user has logged in using the same IP address. In this case,
event variables used to derive the aggregated variables are IP address and user.
public AggregatedVariablesImportanceMetrics getAggregatedVariablesImportanceMetrics()
The variable importance metrics of the aggregated variables.
Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
calculate the number of times an user has logged in using the same IP address. In this case, event variables used
to derive the aggregated variables are IP address and user.
Account Takeover Insights (ATI) model uses event variables from the login data you provide to
continuously calculate a set of variables (aggregated variables) based on historical events. For example,
your ATI model might calculate the number of times an user has logged in using the same IP address. In
this case, event variables used to derive the aggregated variables are IP address and
user.
public TrainingResultV2 withAggregatedVariablesImportanceMetrics(AggregatedVariablesImportanceMetrics aggregatedVariablesImportanceMetrics)
The variable importance metrics of the aggregated variables.
Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
calculate the number of times an user has logged in using the same IP address. In this case, event variables used
to derive the aggregated variables are IP address and user.
aggregatedVariablesImportanceMetrics - The variable importance metrics of the aggregated variables.
Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
calculate a set of variables (aggregated variables) based on historical events. For example, your ATI
model might calculate the number of times an user has logged in using the same IP address. In this case,
event variables used to derive the aggregated variables are IP address and user.
public String toString()
toString in class ObjectObject.toString()public TrainingResultV2 clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojoProtocolMarshaller.marshall in interface StructuredPojoprotocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.