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optuna


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Author: Takuya Akiba
License: MIT License Copyright (c) 2018 Preferred Networks, Inc. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Softwar...
Summary: A hyperparameter optimization framework
Latest version: 3.4.0
Required dependencies: alembic | catboost | colorlog | numpy | packaging | pyyaml | scipy | sqlalchemy | tqdm
Optional dependencies: ase | asv | black | blackdoc | boto3 | botorch | cma | cmaes | coverage | distributed | fakeredis | fastai | flake8 | fvcore | google-cloud-storage | isort | kaleido | lightgbm | matplotlib | mlflow | moto | mypy | mypy-boto3-s3 | pandas | pillow | plotly | pytest | pytorch-ignite | pytorch-lightning | redis | scikit-learn | scikit-optimize | shap | sphinx | sphinx-copybutton | sphinx-gallery | sphinx-plotly-directive | sphinx-rtd-theme | tensorflow | torch | torchaudio | torchvision | types-pyyaml | types-redis | types-setuptools | types-tqdm | typing-extensions | virtualenv | wandb | xgboost

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