interface MLSyntheticDataParametersProperty

Language	Type name
.NET	`Amazon.CDK.Mixins.Preview.AWS.CleanRooms.Mixins.CfnAnalysisTemplatePropsMixin.MLSyntheticDataParametersProperty`
Go	`github.com/aws/aws-cdk-go/awscdkmixinspreview/v2/awscleanrooms/mixins#CfnAnalysisTemplatePropsMixin_MLSyntheticDataParametersProperty`
Java	`software.amazon.awscdk.mixins.preview.services.cleanrooms.mixins.CfnAnalysisTemplatePropsMixin.MLSyntheticDataParametersProperty`
Python	`aws_cdk.mixins_preview.aws_cleanrooms.mixins.CfnAnalysisTemplatePropsMixin.MLSyntheticDataParametersProperty`
TypeScript	`@aws-cdk/mixins-preview` » `aws_cleanrooms` » `mixins` » `CfnAnalysisTemplatePropsMixin` » `MLSyntheticDataParametersProperty`

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 { mixins as cleanrooms_mixins } from '@aws-cdk/mixins-preview/aws-cleanrooms';
const mLSyntheticDataParametersProperty: cleanrooms_mixins.CfnAnalysisTemplatePropsMixin.MLSyntheticDataParametersProperty = {
  columnClassification: {
    columnMapping: [{
      columnName: 'columnName',
      columnType: 'columnType',
      isPredictiveValue: false,
    }],
  },
  epsilon: 123,
  maxMembershipInferenceAttackScore: 123,
};

Properties

Name	Type	Description
columnClassification?	`IResolvable` `\|` `ColumnClassificationDetailsProperty`	Classification details for data columns that specify how each column should be treated during synthetic data generation.
epsilon?	`number`	The epsilon value for differential privacy when generating synthetic data.
maxMembershipInferenceAttackScore?	`number`	The maximum acceptable score for membership inference attack vulnerability.

columnClassification?

Type: IResolvable | ColumnClassificationDetailsProperty (optional)

Classification details for data columns that specify how each column should be treated during synthetic data generation.

epsilon?

Type: number (optional)

The epsilon value for differential privacy when generating synthetic data.

Lower values provide stronger privacy guarantees but may reduce data utility.

maxMembershipInferenceAttackScore?

Type: number (optional)

The maximum acceptable score for membership inference attack vulnerability.

Synthetic data generation fails if the score for the resulting data exceeds this threshold.

AWS CDK