Interface CfnAnalysisTemplate.MLSyntheticDataParametersProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnAnalysisTemplate.MLSyntheticDataParametersProperty.Jsii$Proxy
- Enclosing class:
CfnAnalysisTemplate
@Stability(Stable)
public static interface CfnAnalysisTemplate.MLSyntheticDataParametersProperty
extends software.amazon.jsii.JsiiSerializable
Parameters that control the generation of synthetic data for machine learning, including privacy settings and column classification details.
Example:
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import software.amazon.awscdk.services.cleanrooms.*;
MLSyntheticDataParametersProperty mLSyntheticDataParametersProperty = MLSyntheticDataParametersProperty.builder()
.columnClassification(ColumnClassificationDetailsProperty.builder()
.columnMapping(List.of(SyntheticDataColumnPropertiesProperty.builder()
.columnName("columnName")
.columnType("columnType")
.isPredictiveValue(false)
.build()))
.build())
.epsilon(123)
.maxMembershipInferenceAttackScore(123)
.build();
- See Also:
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Nested Class Summary
Nested ClassesModifier and TypeInterfaceDescriptionstatic final classA builder forCfnAnalysisTemplate.MLSyntheticDataParametersPropertystatic final classAn implementation forCfnAnalysisTemplate.MLSyntheticDataParametersProperty -
Method Summary
Modifier and TypeMethodDescriptionbuilder()Classification details for data columns that specify how each column should be treated during synthetic data generation.The epsilon value for differential privacy when generating synthetic data.The maximum acceptable score for membership inference attack vulnerability.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getColumnClassification
Classification details for data columns that specify how each column should be treated during synthetic data generation.Returns union: either
IResolvableorCfnAnalysisTemplate.ColumnClassificationDetailsProperty- See Also:
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getEpsilon
The epsilon value for differential privacy when generating synthetic data.Lower values provide stronger privacy guarantees but may reduce data utility.
- See Also:
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getMaxMembershipInferenceAttackScore
The maximum acceptable score for membership inference attack vulnerability.Synthetic data generation fails if the score for the resulting data exceeds this threshold.
- See Also:
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builder
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