Values.MLSyntheticDataParametersSourceParameters that control the generation of synthetic data for custom model training, including privacy settings and column classification details.
type nonrec t = {epsilon : MLSyntheticDataParametersEpsilonDouble.t option;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.
*)maxMembershipInferenceAttackScore : MLSyntheticDataParametersMaxMembershipInferenceAttackScoreDouble.t
option;The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
*)columnClassification : ColumnClassificationDetails.t option;Classification details for data columns that specify how each column should be treated during synthetic data generation.
*)}val to_value :
t ->
[> `Structure of
(string
* [> `Double of MLSyntheticDataParametersEpsilonDouble.t
| `Structure of
(string
* [> `List of
[> `Structure of
(string
* [> `Boolean of Boolean.t
| `Enum of string
| `String of SyntheticDataColumnName.t ])
list ]
list ])
list ])
list ]