Anonymeter

The Anonymeter is a sophisticated statistical system designed to evaluate privacy risks in synthetic tabular datasets. It includes evaluators that assess the probability of identifying individuals, linking data, and making inferences. These evaluations are crucial for identifying potential risks to data donors after publishing a synthetic dataset.

Fetch existing anonymity scores for model synthetic data:

model.anonymity_score()

Create new anonymity scores for the model via SDK:

model.generate_anonymity_score(
    aux_columns=["Alley","3SsnPorch"],
    control_tag='Training'
)
model.generate_synthetic_datapoints(1000) #pass instance_type for dedicated reesources , defaults to shared resources