DeepBridge Synthetic
Privacy-Preserving Synthetic Data Generation
Standalone Package - No Dependencies on DeepBridge!
This package can be used independently for synthetic data generation. It was extracted from DeepBridge v1.x to provide a focused, standalone solution. See Migration Guide if migrating from v1.x.
Installation
pip install deepbridge-synthetic
Quick Start
from deepbridge_synthetic import Synthesize
# Generate synthetic data
synthesizer = Synthesize(
data=original_df,
method='gaussian_copula'
)
synthetic_df = synthesizer.generate(n_samples=10000)
Features
- Gaussian Copula: Statistical modeling for synthetic data
- Privacy-Preserving: Generate data while protecting privacy
- Quality Metrics: Evaluate synthetic data quality
- Distributed Computing: Uses Dask for large datasets
- Multiple Methods: Various generation algorithms
Documentation
Full documentation: https://deepbridge.readthedocs.io/en/latest/synthetic/
Related Projects
- deepbridge - Model Validation Toolkit
- deepbridge-distillation - Model Distillation
License
MIT License - see LICENSE
Metadata
Release files for deepbridge-synthetic 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| deepbridge_synthetic-2.0.0.tar.gz | 64.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deepbridge_synthetic-2.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 148.4 kB
Release files / deepbridge_synthetic-2.0.0.tar.gz
| Download URL | deepbridge_synthetic-2.0.0.tar.gz |
|---|---|
| Size | 64.8 kB |
| Tags | Source |
|
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Release files / deepbridge_synthetic-2.0.0-py3-none-any.whl
| Download URL | deepbridge_synthetic-2.0.0-py3-none-any.whl |
|---|---|
| Size | 83.6 kB |
| Tags | Python 3 |
|
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