evaluate

evaluate

Classes:

Name	Description
EvaluationParameters	Configuration for evaluating synthetic data quality and privacy.

EvaluationParameters pydantic-model

Bases: Parameters

Configuration for evaluating synthetic data quality and privacy.

This class controls which evaluation metrics are computed and how they are configured. It includes privacy attack evaluations, statistical quality metrics, and downstream machine learning performance assessments.

Fields:

• mia_enabled (bool)
• aia_enabled (bool)
• sqs_report_columns (int)
• sqs_report_rows (int)
• mandatory_columns (int | None)
• enabled (bool)
• quasi_identifier_count (int)
• pii_replay_enabled (bool)
• pii_replay_entities (list[str] | None)
• pii_replay_columns (list[str] | None)

mia_enabled pydantic-field

Enable membership inference attack evaluation for privacy assessment.

aia_enabled pydantic-field

Enable attribute inference attack evaluation for privacy assessment.

sqs_report_columns = DEFAULT_SQS_REPORT_COLUMNS pydantic-field

Number of columns to include in statistical quality reports.

sqs_report_rows = DEFAULT_RECORD_COUNT pydantic-field

Number of rows to include in statistical quality reports.

mandatory_columns pydantic-field

Number of mandatory columns that must be used in evaluation.

enabled pydantic-field

Enable or disable evaluation.

quasi_identifier_count pydantic-field

Number of quasi-identifiers to sample for privacy attacks.

pii_replay_enabled pydantic-field

Enable PII Replay detection.

pii_replay_entities pydantic-field

List of entities for PII Replay. If not provided, default entities will be used.

pii_replay_columns pydantic-field

List of columns for PII Replay. If not provided, only entities will be used.