Wheelodex » Projects » autoviml » autoviml-0.2.2-py3-none-any.whl

autoviml

View on PyPI — Reverse Dependencies (2)

0.2.2 autoviml-0.2.2-py3-none-any.whl

Wheel Details

Project: autoviml
Version: 0.2.2
Filename: autoviml-0.2.2-py3-none-any.whl
Download: [link]
Size: 134875
MD5: 687a9013ed68c6faccd3852c65fd01ca
SHA256: 066a8d5e5280287f9988d8c772a6c2dc55a737c3cfed97ef77007c10eb527dd5
Uploaded: 2025-01-30 01:17:41 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.2
Name: autoviml
Version: 0.2.2
Summary: Automatically Build Variant Interpretable ML models fast - now with CatBoost!
Author: Ram Seshadri
Home-Page: https://github.com/AutoViML/Auto_ViML
License: Apache License 2.0
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Dist: numpy (<2)
Requires-Dist: pandas (>=2.0)
Requires-Dist: scipy (==1.11.4)
Requires-Dist: xlrd
Requires-Dist: matplotlib (>3.7.4)
Requires-Dist: beautifulsoup4
Requires-Dist: emoji
Requires-Dist: ipython
Requires-Dist: jupyter
Requires-Dist: seaborn
Requires-Dist: catboost (>=1.2.7)
Requires-Dist: textblob
Requires-Dist: nltk
Requires-Dist: regex
Requires-Dist: xgboost (<=1.7.6,>=0.82)
Requires-Dist: vaderSentiment
Requires-Dist: imbalanced-learn (>=0.10.1)
Requires-Dist: shap (>=0.36.0)
Requires-Dist: scikit-learn (<=1.5.2,>=0.24)
Requires-Dist: lightgbm (>=3.0.0)
Requires-Dist: networkx (>=3.1)
Requires-Dist: pandas-dq (>=1.29)
Description-Content-Type: text/markdown
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: requires-dist
Dynamic: summary
License-File: LICENSE
[Description omitted; length: 13311 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.1.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
autoviml/Auto_NLP.py sha256=Mb99BUAEoRf3czPDlIFTqb54NBfRCZQD_YqJBZnAr68 102454
autoviml/Auto_ViML.py sha256=zxL0vk-PNKBlq0hPca70lpdHxbt2-dahiGHZmzB7wpM 336521
autoviml/QuickML_Ensembling.py sha256=YSToI6AbUItu_dgK26DElqFP2IZQ-jCLpHop1nmXzaU 12981
autoviml/QuickML_Stacking.py sha256=hw5-1XTMLjTV3EqZVRCWn5Nj_5jPnMeTcldfb0stuN4 10750
autoviml/Transform_KM_Features.py sha256=zZTzLbKMjxHDFR0oVo0xVkKg4kZuj3DATKuUsF9zgM0 6738
autoviml/__init__.py sha256=kYaEx-kM_zPXjJ67rH_VdxMypc6c0lmjnMn7hO4Whbs 1798
autoviml/__version__.py sha256=pMqw0cAFqCNlWlfVagKMaMFozwMxX9US3JcT43PmZVw 410
autoviml/classify_method.py sha256=blhZqZZeGRqYzRWq4hHa9X0M-7mcINT9vmadqe8enyc 18694
autoviml/custom_scores.py sha256=OYl1vhE8ewa4J2pV-FrRixoed_XARlpLwxr057LfFtc 4767
autoviml/custom_scores_HO.py sha256=cRxoWiISYYj5_7BCr5s5B5Qa1wyORGs7sQMcpoIiK00 8277
autoviml/feature_engineering.py sha256=2WN6kBBvXIhTosfpB4C6YmcCLFsECdEproLZrtLgn7c 29284
autoviml/sulov_method.py sha256=6unGvuvSu310RXeiFq-p2TxqtSroqr71AwdF1-VnX2s 15176
autoviml-0.2.2.dist-info/LICENSE sha256=HrhfyXIkWY2tGFK11kg7vPCqhgh5DcxleloqdhrpyMY 11558
autoviml-0.2.2.dist-info/METADATA sha256=FVzetsExS_Tn9f4gs_sNjT75oVxnLIL5CIE_WM60rg0 14738
autoviml-0.2.2.dist-info/WHEEL sha256=GV9aMThwP_4oNCtvEC2ec3qUYutgWeAzklro_0m4WJQ 91
autoviml-0.2.2.dist-info/top_level.txt sha256=p7ljs-UgJoqLlpmcf3vC5Weh_sChkLAPQy9e64QOdx4 9
autoviml-0.2.2.dist-info/RECORD — —

top_level.txt

autoviml