# syntheticdata 0.1.0

* Initial release.
* `synthesize()`: Parametric (Gaussian copula), bootstrap with noise
  injection, and Laplace noise perturbation methods.
* `validate_synthetic()`: Distributional similarity (KS), correlation
  preservation, discriminative accuracy (AUC), and nearest-neighbor
  privacy ratio.
* `compare_methods()`: Benchmark all three synthesis methods on the
  same dataset.
* `privacy_risk()`: Re-identification risk assessment via
  nearest-neighbor distance ratio, membership inference, and
  attribute disclosure.
* `model_fidelity()`: Train-on-synthetic, test-on-real predictive
  performance comparison.
