Class: Aws::CleanRoomsML::Types::MLSyntheticDataParameters

Inherits:
Struct
  • Object
show all
Defined in:
gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb

Overview

Parameters that control the generation of synthetic data for custom model training, including privacy settings and column classification details.

See Also:

Constant Summary collapse

SENSITIVE = 
[]

Instance Attribute Summary collapse

Instance Attribute Details

#column_classification ⇒ Types::ColumnClassificationDetails

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

Returns:



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# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 4721

class MLSyntheticDataParameters < Struct.new(
  :epsilon,
  :max_membership_inference_attack_score,
  :column_classification)
  SENSITIVE = []
  include Aws::Structure
end

#epsilon ⇒ Float

The epsilon value for differential privacy, which controls the privacy-utility tradeoff in synthetic data generation. Lower values provide stronger privacy guarantees but may reduce data utility.

Returns:

  • (Float) 


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# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 4721

class MLSyntheticDataParameters < Struct.new(
  :epsilon,
  :max_membership_inference_attack_score,
  :column_classification)
  SENSITIVE = []
  include Aws::Structure
end

#max_membership_inference_attack_score ⇒ Float

The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.

Returns:

  • (Float) 


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# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 4721

class MLSyntheticDataParameters < Struct.new(
  :epsilon,
  :max_membership_inference_attack_score,
  :column_classification)
  SENSITIVE = []
  include Aws::Structure
end