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Author:
Jan Teichert-Kluge
Summary:
Synthetic datasets for ML benchmarking with controllable complexity, configurable corruptions, and full provenance.
Latest version:
0.2.0
Required dependencies:
numpy
|
scikit-learn
|
scipy
Optional dependencies:
matplotlib
|
mkdocs
|
mkdocs-jupyter
|
mkdocs-material
|
mkdocstrings
|
openml
|
pandas
|
pre-commit
|
pyarrow
|
pytest
|
pytest-cov
|
ruff
|
torch
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