Add a synthetic data generation model called TabCop, as well as its federated version.

[zhrf5]

…ederated version.

Description

Add a synthetic data generation model based on the Gaussian copula, named TabCop. It simultaneously achieves low computational complexity, competitive performance, and privacy.

Motivation and Context

Improve the efficiency of the current statistics-based model and the quality of the synthetic data it generates. Enhance data privacy protection by introducing differential privacy.

How has this been tested?

Use pytest based on the test case in tests/models/test_tabcop.py to test TabCop

Types of changes

• Maintenance (no change in code, maintain the project's CI, docs, etc.)
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.