Wheelodex » Projects » InsurAutoML

InsurAutoML

View on PyPI — Reverse Dependencies (0)

0.2.6 InsurAutoML-0.2.6-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_24_x86_64.whl
InsurAutoML-0.2.6-cp39-cp39-win_amd64.whl

Wheel Details

Project: InsurAutoML
Version: 0.2.6
Filename: InsurAutoML-0.2.6-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_24_x86_64.whl
Download: [link]
Size: 485554
MD5: 2f8d6884b6242e61531ca9e52b24115c
SHA256: a491487c4b058e14ce84d8cb193f2d87084729cf88c7110d344abac15eb3cd63
Uploaded: 2023-12-17 02:53:37 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: InsurAutoML
Version: 0.2.6
Summary: Automated Machine Learning/AutoML pipeline.
Author: Panyi Dong
Author-Email: panyid2[at]illinois.edu
Home-Page: https://github.com/PanyiDong/InsurAutoML
License: MIT
Platform: Linux
Platform: Windows
Platform: MacOS
Requires-Python: >=3.7
Requires-Dist: setuptools
Requires-Dist: threadpoolctl (>2.2.0)
Requires-Dist: cython
Requires-Dist: numpy (<1.24.0)
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: pyarrow
Requires-Dist: fastparquet
Requires-Dist: func-timeout
Requires-Dist: matplotlib
Requires-Dist: seaborn (>=0.11.0)
Requires-Dist: ray (<2.0.0)
Requires-Dist: gensim
Requires-Dist: ray[tune]
Requires-Dist: tqdm
Requires-Dist: tensorboardX
Requires-Dist: scikit-learn (>=1.2.0)
Requires-Dist: redis; platform_system == "Windows"
Requires-Dist: mlflow; extra == "dev"
Requires-Dist: lightgbm; extra == "dev"
Requires-Dist: xgboost; extra == "dev"
Requires-Dist: pygam; extra == "dev"
Requires-Dist: flaml; extra == "dev"
Requires-Dist: bayesian-optimization (==1.4.0); extra == "dev"
Requires-Dist: colorama (==0.4.4); extra == "dev"
Requires-Dist: nevergrad; extra == "dev"
Requires-Dist: optuna; extra == "dev"
Requires-Dist: gensim; extra == "dev"
Requires-Dist: torch; extra == "dev"
Requires-Dist: mlflow; extra == "extended"
Requires-Dist: lightgbm; extra == "extended"
Requires-Dist: xgboost; extra == "extended"
Requires-Dist: pygam; extra == "extended"
Requires-Dist: flaml; extra == "extended"
Requires-Dist: bayesian-optimization (==1.4.0); extra == "extended"
Requires-Dist: colorama (==0.4.4); extra == "extended"
Requires-Dist: nevergrad; extra == "extended"
Requires-Dist: hyperopt; extra == "extended"
Requires-Dist: optuna; extra == "extended"
Requires-Dist: rpy2; extra == "extended"
Requires-Dist: gensim; extra == "nn"
Requires-Dist: torch; extra == "nn"
Requires-Dist: rpy2; extra == "nn"
Provides-Extra: dev
Provides-Extra: extended
Provides-Extra: nn
Provides-Extra: normal
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 12518 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.42.0)
Root-Is-Purelib: false
Tag: cp39-cp39-manylinux_2_5_x86_64
Tag: cp39-cp39-manylinux1_x86_64
Tag: cp39-cp39-manylinux_2_24_x86_64

RECORD

Path Digest Size
InsurAutoML/constant.py sha256=PlknojlHDEWN9NJjxfOkp-RQtk1ZibNZl9ekOWVzw34 6457
InsurAutoML/base.py sha256=QvYuEhROxqZYG9Yw7yIzZQD9iXHd__7XTz-3GIz2HgE 9725
InsurAutoML/__init__.py sha256=dLydzgesXgPobWxsAJdGhpOQ3Dqf-WxDguqtPbBBAsA 6317
InsurAutoML/version.py sha256=c9CeRKFFZOFlW99IKxM9evkWtZ6qfnu7MlEZWpENryg 1828
InsurAutoML/imputation/multiple.py sha256=8p1_zhPhqLE5cnxqPYssQP8phCkqtWRYz-P1rJBixvM 19724
InsurAutoML/imputation/base.py sha256=Tf7pJt8mV3OTVk9P2olOgYIzK6JRqL74wkxMDWx7jSc 9585
InsurAutoML/imputation/__init__.py sha256=iZXzyUSiXGDTzWnL9_1B9D9OoXDu6ulizlhCWMoxujE 2718
InsurAutoML/imputation/nn.py sha256=Gtus3SQeKW_mcazaopa5Nd191eIVq72mFXVM1248-L0 26464
InsurAutoML/imputation/clustering.py sha256=J_5qBqnjrdD_W70weXSO_QQALKAdm-9AU7tkA710K1o 40376
InsurAutoML/balancing/base.py sha256=iHxK1nJk11PPQWOC34LGFLTKpxbsdnPL4oPQ5kKK1Vs 1971
InsurAutoML/balancing/under_sampling.py sha256=kSGKLR3dxGT-syV8l4tL40MavYooKKQ7AqVrM75AOd4 24496
InsurAutoML/balancing/__init__.py sha256=hIY9R66W8HRsmMObUbjxpfihHU4aUHlA-V5udTTmi68 2618
InsurAutoML/balancing/over_sampling.py sha256=EidJnt6bFEHwaYgjWd7Jc3KPku_UtwuIhMwcjduXrOc 10185
InsurAutoML/balancing/mixed_sampling.py sha256=bVbkV2FJDSqwZN1dS-kMK5xrKoYzdCxFnrr_qu6NxIg 6999
InsurAutoML/datasets/text.py sha256=5hguv9rADFu5mtIfj-HIc2EEX0JLYzIbOEhGVv5aPTM 4199
InsurAutoML/datasets/image.py sha256=28EM3oU9gq_UB51062GJ5_8rJQDA9oHg9T2-plCd-KU 3037
InsurAutoML/datasets/__init__.py sha256=zdM5Y1RBrez9ZN0VZkSl_nz49-ANpFe08ka8jZJVfDA 3408
InsurAutoML/datasets/tabular.py sha256=-by7xEWwV1l3LofAlRRorFByBlNbXJNBdiHo3I7yG3U 80019
InsurAutoML/encoding/encoding.py sha256=kOfMoVtsC4y1bqA2E3_NwOGvostOYbXzqcHN1634KPA 11413
InsurAutoML/encoding/base.py sha256=BuZbSlyAAfYROm3bHPfxAQFkru5uZT12oLwvvJK6hHY 1748
InsurAutoML/encoding/__init__.py sha256=x4bJw59GxpNfL2LKg-135n68LTu59F6dvhsgAfs_D24 1646
InsurAutoML/utils/base.py sha256=_7Y5-lMXQ4GCc0axei4dpI1FAfs9O3cqqi6YF1JYNGE 11996
InsurAutoML/utils/file.py sha256=0uCjUKOalFJsHmrRGB0IxrjVrUjgl40nFNejnvOlUDs 3559
InsurAutoML/utils/__init__.py sha256=o1oPk6Jx71ZEb4ifS2b2aj1g_2c0BNa74-_Z1AuWpfg 2206
InsurAutoML/utils/eda.py sha256=0g_at_ju8en3BHq0E9w8sPRomeMoFx1img6q8hCAnAI 8965
InsurAutoML/utils/stats.py sha256=ymCh67ayI15r3qya5kK2iDVaUL8c08Uj-D4ot_NPgRM 15053
InsurAutoML/utils/metadata.py sha256=7v49tEzzYjoa2g9VsP_rPcJompvUenpnw0XXoe_dgb4 14347
InsurAutoML/utils/data.py sha256=JaPdqlEQeXLa5JOOQoq24Lx9AAGszqJPxbEvXkdNPrA 27683
InsurAutoML/utils/optimize.py sha256=aw2V1hqJ86pIwUfocsLAJxrB9Njqez5i1qkzqmGqf1M 65083
InsurAutoML/utils/tensor.py sha256=xedL6uOHh6zg720aMWT-A5XmTx1-lb3SbNrjSrNBTDM 8500
InsurAutoML/utils/_c/_stat.cpython-39-x86_64-linux-gnu.so sha256=GYd8Ki_mEqcuJUxyxM-WFaaEzSQLztgsGEI4-AEqlMM 65008
InsurAutoML/utils/_c/_base.pyx sha256=k6W216uA6tfMZFkiZeYkhyYuJuHIKMvBj_cLIAcl1fE 4365
InsurAutoML/utils/_c/__init__.py sha256=XRGPsqTMhofbmt3pao8g8VXYDtItNFz7fZtO3gSpRrQ 1761
InsurAutoML/utils/_c/_stat.pyx sha256=lMur0mHlaK4szGCBqtlunsokofee1O8QVmf-RodSIbk 1537
InsurAutoML/utils/_c/_base.cpython-39-x86_64-linux-gnu.so sha256=cBH4PIaZvHVB5Glq2_rb5EJMytshCkq6AfrPv_Izd2A 540288
InsurAutoML/feature_selection/sklearn.py sha256=wwDviRLTpqmPDRx5KcX2U9EM5wx5Fy3nEoULr8CL2S4 27673
InsurAutoML/feature_selection/base.py sha256=ZvLkfAcXiq043u91ixY8S_-ILPUdvmxPcVnX4I02BtI 2610
InsurAutoML/feature_selection/hybrid.py sha256=lS1oN2x3yaQ1L-ZTrShArwTe9D_KY7nd_nJNgEw_GaM 30267
InsurAutoML/feature_selection/__init__.py sha256=yzKTZBxNYnf1kwdGeH3bBgHLM5ZA4ea_rrjtQnlIZJ4 6189
InsurAutoML/feature_selection/embed.py sha256=qCtS8xyAh6Vkcxr6c5DgqTlmZe07hTDCYtN0WxaZsQI 13728
InsurAutoML/feature_selection/autosklearn.py sha256=f-IpiaWzaS2olhhM_eJaUihdQOzvTu733XZUVvTQQm0 17110
InsurAutoML/feature_selection/filter.py sha256=yxGCv34rOM5puIMpH7bcRC5_JJhwlh1D8FIFE6V4984 9918
InsurAutoML/feature_selection/wrapper.py sha256=CkgBQlbaKEA4ee2hhHCh8VkUIWNTIVaH1XKa9mQIiEo 18929
InsurAutoML/model/RNN.py sha256=FVKtRT7uJwneB9R_S5scymah7Qc5nj9nSFTTDkj9tcE 20353
InsurAutoML/model/lightgbm.py sha256=ubss_8T-v8QEFzj2GfLH4EQgZYSCWUc7-55dqf6k2Xo 15036
InsurAutoML/model/base.py sha256=JQM86NZ1rLHByWmNkny6q2aAitqpkcLyOs9AI8IYXMo 4002
InsurAutoML/model/sklearn_classifiers.py sha256=vco2beaU2mGRmHfBXxdvsFbVsKlCNkO5fpqj9Qx0JaQ 43436
InsurAutoML/model/xgboost.py sha256=YMQsccLWY2E4mWDELQHqCTmQtHCnm4w9rUaPL62qkZg 8819
InsurAutoML/model/__init__.py sha256=gtOujCkjBBdbaGyEVvaPMn0G_kEQTJJtplrcV0RQnWo 10566
InsurAutoML/model/ML.py sha256=p2lP_OFtdFJQtodJZCCpgoPR1l19Yw1ylKr4P5-KC8E 1526
InsurAutoML/model/gam.py sha256=CBT73P-DH0UwRekWyGDOuKniMsDj9xfxHjRKUUV71O4 4082
InsurAutoML/model/sklearn_regressors.py sha256=QRBYs0WWND_1fiGvBHGa8O3v4s3qnFQZl3PGAlfNe3I 41314
InsurAutoML/model/autosklearn.py sha256=Op4r3zCsFcv8aJ0D8jd_vYKbcwgjJ7PqnZZnTQjDmGc 45340
InsurAutoML/model/FNN.py sha256=51RCxG_LDT4bGLeMmwS1_RltQZVeYtGP8FNIOIVU2cs 16895
InsurAutoML/model/clustering.py sha256=8rfYA7U_RJH7lWwtzlPLYxi4EYEJXdMhmekcJZev8ok 2287
InsurAutoML/scaling/scaling.py sha256=FGMIZGGhWsu5xUx8Pj55Ezpt7KJwpuc2fTYK0Yq4nYg 26337
InsurAutoML/scaling/base.py sha256=MLpCcszsyQherrqt3wJiDFRPhZXsUMnjM48x22MY-uI 918
InsurAutoML/scaling/__init__.py sha256=F743rN9zvxKmSWTS6MD098EEKm9vhdwGkisLqIat9Is 2360
InsurAutoML/hpo/base.py sha256=t8vaizKOg8K9cvvuv9W2tfe7bqDE8dhhsva4CyNpJx8 84231
InsurAutoML/hpo/DL.py sha256=JApErM6dulpmjfsREp2iAYBDLh1M0H5JT2qO2c7rl0c 2453
InsurAutoML/hpo/utils.py sha256=BCVhNF6mpNWVFg4H6nfYEb26WHKA38wAmmSXKJftv84 20963
InsurAutoML/hpo/ensemble.py sha256=3H7RDH8Z1l6bcahK8l6ML2b8ZSv3lEBcO0pwbaTakLo 16708
InsurAutoML/hpo/__init__.py sha256=fTJAaQlc8tnsqZf0jPtD0gXfTf7-1UcjKR2xF5Uh9m0 1853
InsurAutoML/hpo/ML.py sha256=Ugyc22rg-8w8jBj0Hd5RUGl3I4h95XxU1_YlPx1I3-Q 35395
InsurAutoML/hyperparameters/__init__.py sha256=iliLaQjdqHdRhZhsAY2jlOZmSEdxYoYI3qyLbiFja04 6670
InsurAutoML/hyperparameters/_hyperopt/_balancing_hyperparameter.py sha256=GDVi8-_TdVRGTrnrlr9_U31P7E-gc0txgxtlGCtClzo 3644
InsurAutoML/hyperparameters/_hyperopt/_encoder_hyperparameter.py sha256=_4O9d9l31VvEHfvjOF2SriLf-Wy6SB0kI_eS4MqeUBQ 1638
InsurAutoML/hyperparameters/_hyperopt/_imputer_hyperparameter.py sha256=kxc3HeeEmmDqCjm3cgSAoynW-pmH1FOtBbMOtuGM-Nw 2630
InsurAutoML/hyperparameters/_hyperopt/__init__.py sha256=RGo2idpHkwrr4xUbdmza4MlYUMShrP4DaTCV5eYAW5A 1997
InsurAutoML/hyperparameters/_hyperopt/_regressor_hyperparameter.py sha256=BLWn5NFtWrAerdENOxnnvd-Kl__kJCYJkOasAm1-pP4 12742
InsurAutoML/hyperparameters/_hyperopt/_scaling_hyperparameter.py sha256=nrGGZk1zONChaIVTUx3vfkGCztUh7CxC2I5WhNMt4zc 1958
InsurAutoML/hyperparameters/_hyperopt/_feature_selection_hyperparameter.py sha256=2x-C7eh5w3JKxyyAKcfwW13KRSfsvM-1Z4J_-I9JCwg 11148
InsurAutoML/hyperparameters/_hyperopt/_classifier_hyperparameter.py sha256=jvWX0Ei6NrG-KthOmahnb7NYDw0axoADjokBMlBoCfM 12623
InsurAutoML-0.2.6.dist-info/WHEEL sha256=NlzZs1_xAAN2E9XlgBSm4cnBA0-S5IaciyB_EgwIheI 181
InsurAutoML-0.2.6.dist-info/LICENSE sha256=OkANZW_dNr-tuv1SsqPLP2lX5FBjQaOWoL15_DkaA2Q 1066
InsurAutoML-0.2.6.dist-info/RECORD — —
InsurAutoML-0.2.6.dist-info/top_level.txt sha256=4t7qOgeK6uywJk8xNB-dmMf008-kFssEVa4XBbny1lw 12
InsurAutoML-0.2.6.dist-info/METADATA sha256=owh368pnFb9gWq5JsozX9QUFJ_s4_qrQyKzXumBEQVs 14566

top_level.txt

InsurAutoML