How to evaluate the quality of synthetic data: fidelity, utility, and privacy
- The problem
- Regulated firms cannot freely use real data, but synthetic data is only useful if you can trust it.
- Why it matters
- A framework for measuring synthetic data on fidelity, utility and privacy.
- Who should read it
- Data scientists, privacy officers
- What you'll get
- An evaluation method for synthetic datasets.
- Series
- Synthetic Data, Part 1 of 2
The full article lives on AWS Blog. This page is a short guide to what it covers.