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tune-easy

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0.2.1 tune_easy-0.2.1-py3-none-any.whl

Wheel Details

Project: tune-easy
Version: 0.2.1
Filename: tune_easy-0.2.1-py3-none-any.whl
Download: [link]
Size: 52295
MD5: 47a6f68b06fac043732fb621727670f9
SHA256: 616c44d4022f0be828aae9c38018e09e042a685ea9db3ec6abacb4b2d49f7a4e
Uploaded: 2022-04-29 17:50:24 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: tune-easy
Version: 0.2.1
Summary: tune-easy: A hyperparameter tuning tool, extremely easy to use.
Author: Kenta Nakamura
Author-Email: c60evaporator[at]gmail.com
Maintainer: Kenta Nakamura
Maintainer-Email: c60evaporator[at]gmail.com
Home-Page: https://github.com/c60evaporator/tune-easy
Download-Url: https://github.com/c60evaporator/tune-easy
License: BSD 3-Clause
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Multimedia :: Graphics
Classifier: Framework :: Matplotlib
Requires-Python: >=3.6
Requires-Dist: scikit-learn (>=0.24.2)
Requires-Dist: matplotlib (>=3.3.4)
Requires-Dist: seaborn (>=0.11.0)
Requires-Dist: numpy (>=1.20.3)
Requires-Dist: pandas (>=1.2.4)
Requires-Dist: optuna (>=2.7.0)
Requires-Dist: bayesian-optimization (>=1.2.0)
Requires-Dist: mlflow (>=1.17.0)
Requires-Dist: lightgbm (>=3.3.2)
Requires-Dist: xgboost (>=1.4.2)
Requires-Dist: seaborn-analyzer (>=0.2.11)
[Description omitted; length: 5577 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.36.2)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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tune_easy/_group_time_split.py sha256=BXX1Fgb5dieMLtVFqF6pEGRdNail1ij0JAE8tspgz9I 3784
tune_easy/_util_methods.py sha256=_uUowOOxCoY7-yLmsBjTctnwIcMZO50BZr7m9rdpDKA 1629
tune_easy/all_in_one_tuning.py sha256=I6r0LAYLM9Sm38CbBFUmUsQBEpajHZlbwMWQdRdnWWA 53195
tune_easy/elasticnet_tuning.py sha256=v5-OjH6CF9ge9H5tyBslh1CSqx5lE3g1EIB4oChnl64 3545
tune_easy/lgbm_tuning.py sha256=ymvk3WRWHG3BYjr1yn7HXj4fun2j7L2x3ziJbhtFJ7s 18085
tune_easy/linearregression_tuning.py sha256=AW6xpkMwtjKmf70FXeFNqqiPnfrElOGv0Rc3zodEsug 3163
tune_easy/logisticregression_tuning.py sha256=f6kK9zKOB3oZGd4CZbyB1XBBgsP6LkQFrTH0WFuZd5g 3210
tune_easy/param_tuning.py sha256=O0VL6gt5OlcYH7hRmBUQWyr8pIXUHNjyJ9NrjHgMYfU 117905
tune_easy/rf_tuning.py sha256=515C8OM38B0-48IL2dylqqEsML3nSSpafWHb2Qei5h8 11875
tune_easy/svm_tuning.py sha256=21_sjzOtniA14r52rvRyTaMMPBD9xC081FgjvY2sCTU 6916
tune_easy/xgb_tuning.py sha256=-X7mFIqhWnuCvgUStRZ1HtdzSLD6JDVFPdYBjKn_JbI 19755
tune_easy-0.2.1.dist-info/LICENSE sha256=tMEqV1g6BNMWoL_yOTlT7IycOa-4C1i86AnWBDkfKG0 1551
tune_easy-0.2.1.dist-info/METADATA sha256=-_P59-ar9fVSsLHRgv3xKzRokwz3K2JO8kLlE9WhRK0 7064
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tune_easy-0.2.1.dist-info/RECORD — —

top_level.txt

tune_easy