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Author:
None
Summary:
A modular framework for evaluating synthetic tabular data quality, utility, and privacy preservation
Latest version:
1.1.0
Required dependencies:
click
|
imbalanced-learn
|
matplotlib
|
numpy
|
pandas
|
pgmpy
|
pyyaml
|
rich
|
scikit-learn
|
scikit-posthocs
|
scipy
|
sdv
|
seaborn
|
smartnoise-synth
|
torch
Optional dependencies:
catboost
|
hypothesis
|
lightgbm
|
mkdocs-material
|
mkdocs-minify-plugin
|
mypy
|
optuna
|
pre-commit
|
pytest
|
pytest-cov
|
ruff
|
xgboost
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