Wheelodex » Projects » causalml

causalml

View on PyPI — Reverse Dependencies (1)

0.15.2 causalml-0.15.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
causalml-0.15.2-cp39-cp39-win_amd64.whl
causalml-0.15.2-cp39-cp39-macosx_10_9_x86_64.whl
causalml-0.15.2-cp39-cp39-macosx_11_0_arm64.whl
causalml-0.15.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
causalml-0.15.2-cp38-cp38-win_amd64.whl
causalml-0.15.2-cp38-cp38-macosx_10_9_x86_64.whl
causalml-0.15.2-cp38-cp38-macosx_11_0_arm64.whl
causalml-0.15.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
causalml-0.15.2-cp311-cp311-win_amd64.whl
causalml-0.15.2-cp311-cp311-macosx_10_9_x86_64.whl
causalml-0.15.2-cp311-cp311-macosx_11_0_arm64.whl
causalml-0.15.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
causalml-0.15.2-cp310-cp310-win_amd64.whl
causalml-0.15.2-cp310-cp310-macosx_10_9_x86_64.whl
causalml-0.15.2-cp310-cp310-macosx_11_0_arm64.whl

Wheel Details

Project: causalml
Version: 0.15.2
Filename: causalml-0.15.2-cp39-cp39-win_amd64.whl
Download: [link]
Size: 2257571
MD5: 91021ff552647b972aa57c20733e195c
SHA256: eb7357a35cfabd41bed671b8e5f583f30be525b111432a47e8158ee5ed0fc2dd
Uploaded: 2024-10-01 06:25:29 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: causalml
Version: 0.15.2
Summary: Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms
Author: Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Jing Pan, Mike Yung, Zhenyu Zhao
Maintainer: Jeong-Yoon Lee
Project-Url: homepage, https://github.com/uber/causalml
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Requires-Dist: forestci (==0.6)
Requires-Dist: pathos (==0.2.9)
Requires-Dist: pip (>=10.0)
Requires-Dist: numpy (<2,>=1.18.5)
Requires-Dist: scipy (>=1.4.1)
Requires-Dist: matplotlib
Requires-Dist: pandas (>=0.24.1)
Requires-Dist: scikit-learn (>=0.22.0)
Requires-Dist: statsmodels (>=0.9.0)
Requires-Dist: Cython (<=0.29.34)
Requires-Dist: seaborn
Requires-Dist: xgboost
Requires-Dist: pydotplus
Requires-Dist: tqdm
Requires-Dist: shap
Requires-Dist: dill
Requires-Dist: lightgbm
Requires-Dist: pygam
Requires-Dist: packaging
Requires-Dist: graphviz
Requires-Dist: pytest (>=4.6); extra == "test"
Requires-Dist: pytest-cov (>=4.0); extra == "test"
Requires-Dist: tensorflow (>=2.4.0); extra == "tf"
Requires-Dist: torch; extra == "torch"
Requires-Dist: pyro-ppl; extra == "torch"
Provides-Extra: test
Provides-Extra: tf
Provides-Extra: torch
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 8713 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.1.0)
Root-Is-Purelib: false
Tag: cp39-cp39-win_amd64

RECORD

Path Digest Size
causalml/__init__.py sha256=mvK5dbJZ37wFo0D_rndIh9ImNrS1F6kuHaAkYXVKVfo 159
causalml/features.py sha256=l856ks7EeUPDWPSXaq3jJVw1TruKW4tBT7eZJzq1eyk 8456
causalml/match.py sha256=HWceZ9p2ZXF4Mh2Wh8cPsqjnmmbMBwdUIpZHU2MO43A 20238
causalml/propensity.py sha256=EKTlS0tSIszl7bnVd1HqGPOnA92hbwvU6j35Z6RFE9E 7255
causalml/dataset/__init__.py sha256=XQGoUk37RU6oC1-9IN1M3U1uz-Y_DU9178p6GEnOr0E 888
causalml/dataset/classification.py sha256=F2677fmHvg-Ih1W81k8Xn6Ud58is2BX1MKdg8d6CmoQ 29538
causalml/dataset/regression.py sha256=uMhNki_TVFpfyq87PjUSY0FzEYsFeML3X4GWX4ykltI 9069
causalml/dataset/synthetic.py sha256=C8LtDJL9o_T25RE8Xheu4BTtNv-Oy8Yv_De2ITkb-HU 25060
causalml/feature_selection/__init__.py sha256=MebIMtAHAlqxZ5SxhfcqHnYUfHOnIrePrHt3lWYm4T4 35
causalml/feature_selection/filters.py sha256=WdTFCAkEInUXWJQcVUe1jNheh5PylY-oeISGiinz96s 28339
causalml/inference/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
causalml/inference/iv/__init__.py sha256=30tWHSKz3g1OJkO7js-CNT95DHMlS1g0f6ymjondcn0 119
causalml/inference/iv/drivlearner.py sha256=ysm5yrzL5fVQcv-tGIGNNZ2jlGZiCvzLDERHV7cz6Pk 38594
causalml/inference/iv/iv_regression.py sha256=OKWE7PLuk9kKRbb-Wcz_ZY1KrX3TrDeez4rpAFAS2Hs 1468
causalml/inference/meta/__init__.py sha256=N5876qiM9lB5kRe1qayo01WaSKCqMMBSIpB9CFTIaiY 468
causalml/inference/meta/base.py sha256=kIiylVOAJeZYK-c_Q3N1H0tN0AP4Cy70oV9S14ThkgM 13815
causalml/inference/meta/drlearner.py sha256=5avFjSvwp3VICM6L1r4QLziUleLvuvQU4IHGxwnElYs 20459
causalml/inference/meta/explainer.py sha256=XvMuZVPMQszp-4SMVbj21UkgxASgbeJs1lJ0MPt5AQg 11750
causalml/inference/meta/rlearner.py sha256=e2ngZ4HStMz8IVra-Q6he6WA9QI8TBlHXWY14zlR7K0 29869
causalml/inference/meta/slearner.py sha256=H1ycpUavLJYJknXn4HDKmUNp6b2CqtrYoJt3VSxF7n4 16280
causalml/inference/meta/tlearner.py sha256=obxmPPDsImqwN7aUZI-ZWOnZ6tM0eua8mXApzYOZ3TA 16130
causalml/inference/meta/tmle.py sha256=5I0moE-xnY8zm0BWeY2Oj_fzZev_oMbne0ALY7DC23Y 8537
causalml/inference/meta/utils.py sha256=tRfUCnFhGIxhUA_Aj9vo--RCSOWX4V5qqMQZxY_fw60 4412
causalml/inference/meta/xlearner.py sha256=3nu0IHQ500NpxscEMGBqK2ospV5gTw6bf1YA7poDUAc 27271
causalml/inference/tf/__init__.py sha256=03pgNHSSte4lACWy4IRZEDuhcQBgnncRWnrQWzwkC7A 34
causalml/inference/tf/dragonnet.py sha256=yIEjC3cTkgPYjpBfO-tpSPe1G6nI6OqsNDNJNEf2wVE 10924
causalml/inference/tf/utils.py sha256=RV0w_AVmgxNifxASo-tJAr4qvyi0MuVfTxf3rKTwJA4 6270
causalml/inference/torch/__init__.py sha256=xyvGx5Kvdo-BbQrDjN6LYmFMCNb-OnzQ2JJeBS-OYCE 26
causalml/inference/torch/cevae.py sha256=ntB9zpu1ztDLiubFf5eDhp9dsOa9qo38JM7X_8j5Au8 5612
causalml/inference/tree/__init__.py sha256=ygZv7uiJXKk-l3HeJtxfnnYGRX3j1_Ga5mwbyDLHsuQ 435
causalml/inference/tree/plot.py sha256=L7iXJiYVlDw4Eo8mHv65mXu71l6hx-3HLG2p-N_6hso 24729
causalml/inference/tree/uplift.c sha256=sABXUb5KT0bWepbJNWTq7nlb6WCiUIKOJat7xM7kljQ 2741845
causalml/inference/tree/uplift.cp39-win_amd64.pyd sha256=cVRyEsBBzhHfaDfl_2zCzfpaitD6sTL3fNesWR8c0bA 569856
causalml/inference/tree/uplift.pyx sha256=0HlAUr6hCr66Vw8ygZ-fMtjX5ci6hbrcBrWlak20ecY 111497
causalml/inference/tree/utils.py sha256=1yUfchhjffuJbp6Y1iuaxt2bIeujhZWNkX1J5QOaSPs 11375
causalml/inference/tree/_tree/__init__.py sha256=XmiH9t4qicpgX-FZtVcbVDseju9sdCMctOXQ9tqYNSk 149
causalml/inference/tree/_tree/_classes.py sha256=zCp5kM77FikXuB0k1kr9wf5dGfmP3kr16sLgYMCbmPs 11321
causalml/inference/tree/_tree/_criterion.c sha256=8d6tR5U8iLXz5_8m6m2GFMNAc5Ynktzmp51QH-3gBCE 1064099
causalml/inference/tree/_tree/_criterion.cp39-win_amd64.pyd sha256=fwsEKT7XDZ8ubEnIeSznnQRbsGHC-QiSH7rpeQQ3kCQ 131584
causalml/inference/tree/_tree/_criterion.pxd sha256=hjx41talmj8qV18yCOpOrWCjmzQ_zAxblowjLqVS4pQ 3854
causalml/inference/tree/_tree/_criterion.pyx sha256=Mi4hVNUuHv4fJXkz64LuNE3e37pr_HOIswSgnWZSUds 13968
causalml/inference/tree/_tree/_splitter.c sha256=GNFSj0qd1NS6-EesaqybSIpXUVXqPhCJWpe6f6A2L3k 1574980
causalml/inference/tree/_tree/_splitter.cp39-win_amd64.pyd sha256=c_tLVO-z84pKiUjdZTMo6KZoXxsMASgUnNPNejEESt0 184320
causalml/inference/tree/_tree/_splitter.pxd sha256=f4v_36RvHo2rDpGPd5EbT4kY0F4vmKYpfw_1bnCVdxc 4373
causalml/inference/tree/_tree/_splitter.pyx sha256=VXXqWJk3jGaSQjdbQ_u5RZsHOoyaLEYKJOoxBlRxpqA 62695
causalml/inference/tree/_tree/_tree.cp39-win_amd64.pyd sha256=iDvcBEWCbmDwoUSycVPHdQfcD8y6RU-CBc_1b82naYU 372224
causalml/inference/tree/_tree/_tree.cpp sha256=IWTKcKULCte1m_w7ZCZCf5rLLVKVTlBxCmoBjBCepwY 2234973
causalml/inference/tree/_tree/_tree.pxd sha256=8qNNZrjwTFoO2tynuhs-tcEL0mQM0fb_vd6wVepbAik 4732
causalml/inference/tree/_tree/_tree.pyx sha256=ikASih5L4PmJMjLoh7rotmUJUS29YG5eYcVfts-GIMY 68206
causalml/inference/tree/_tree/_utils.c sha256=904NQGeDGmazOdWu_Ay91WnMNZ6BNdvBqMRVpoaKxek 1085248
causalml/inference/tree/_tree/_utils.cp39-win_amd64.pyd sha256=Z9NW41QJOyZ-1gJxNUJ4u2v6pAqsK1ClmtXIuLLrF-M 134656
causalml/inference/tree/_tree/_utils.pxd sha256=kZWVIXhK0sGzba95HgboWfM-1DAiANe3Mlxo7mDBvB4 3093
causalml/inference/tree/_tree/_utils.pyx sha256=R9oRqu4WZmjz4kdKykwZNR3zOsNjtiHSnGhh0EFMuTk 3604
causalml/inference/tree/causal/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
causalml/inference/tree/causal/_builder.cp39-win_amd64.pyd sha256=3qSu5KOeEsZoWNgQ6lXrG-kIkKnhCr8Kmf_nkn-uXa4 176128
causalml/inference/tree/causal/_builder.cpp sha256=jWRdhoF7GwwdRy8GW7pqv8X-WWT2FR5g_sfw1VnK3_Q 1219993
causalml/inference/tree/causal/_builder.pxd sha256=pCSy1-GXiJB6Z4ubUWP_lYtQ3oNKJu7wX4ZDIZbEiHg 290
causalml/inference/tree/causal/_builder.pyx sha256=uXyjj4Ey02FmrDuo8zfdtZWlWkX1ze6_PrA-3jfcAro 16600
causalml/inference/tree/causal/_criterion.c sha256=Kr_QyPS5QIdhz9AAQkZBaGy7ZaHzoJh-4iODy7kArpM 1261974
causalml/inference/tree/causal/_criterion.cp39-win_amd64.pyd sha256=ynFaA8Amllgd3f_BzQ3_G1LmOoedmdtWvzX6igqGGRo 150528
causalml/inference/tree/causal/_criterion.pxd sha256=pCgjQd6ISPkjGOWUESHN8u8t1K_QurMq0V2e1PTsPjE 981
causalml/inference/tree/causal/_criterion.pyx sha256=RqOU22e8ZsFcaSX__s-lTjI4blHeeP6fJJZ30VLI9cE 21002
causalml/inference/tree/causal/_tree.py sha256=yhyFMPvIq_Pu9jc3tZdpYwgRMAGHy1F6y1UohZZVUVM 10103
causalml/inference/tree/causal/causalforest.py sha256=POyl6NCiBXHhKrVHWcvOVU8Z3TAEN8Z7tE28byMRu98 19527
causalml/inference/tree/causal/causaltree.py sha256=zTL4vn8MfT22ouc2IVHJqkD8FqlcHA-usAThwForbZ0 16731
causalml/metrics/__init__.py sha256=UmoCcYTOp7GpprcfslBoEovhelGDAHKAdRL4ikIXdA8 777
causalml/metrics/classification.py sha256=K1UWf8FCLA4Jm_cVA-S5cHpvXSAnvFoJLg3e533RUK4 1013
causalml/metrics/const.py sha256=Dda7zqiB10uKzNYBJ-OG4hb3b1v_17hojtkJo958ZRg 13
causalml/metrics/regression.py sha256=XTUaNX02vRIT5mGemPh543-qbISEDU4SsWFQIvbbqu8 3321
causalml/metrics/sensitivity.py sha256=mcqQ_lLKmoG1mR79F1b2gz4F4B4dfAuFsewCnr6GAuE 22880
causalml/metrics/visualize.py sha256=wOaxDOHfAwUrBgse8p1lMFD4zwBLKghIzZI8sqxOrV4 38101
causalml/optimize/__init__.py sha256=VvzN18bgXDinRXjNyUzq_bnIz7x_aB1umzhRlDBIbX4 268
causalml/optimize/pns.py sha256=3czte1wXZv-E0-3MN6CQj8DHEmU0Kkzn5t0TZ8sy50g 2840
causalml/optimize/policylearner.py sha256=iQXISBE2y9YigztAsQqO8x4PkMrEX5oQV9eSCB3eHLE 6147
causalml/optimize/unit_selection.py sha256=Ic_aagoLB4C9smIq5syG7c7tco2vhYWFqnkvqvPhGbc 9718
causalml/optimize/utils.py sha256=CTEOyDzagw1nLuysmmMt-wg54bKLNkmiiuxOnIhkd8M 4347
causalml/optimize/value_optimization.py sha256=exYURPXwoM8B5H4mXCtWWg1bscbTLoU56bKhJd_eRG4 4212
causalml-0.15.2.dist-info/LICENSE sha256=d-L4vudcIOzEMKptjoFiLQFyBMmG_fp49cjUHsaPHzU 573
causalml-0.15.2.dist-info/METADATA sha256=B5DT4g5gqIYuCjBxgUxJf5Kh3HSi0dB0--eTDiZQpsk 10256
causalml-0.15.2.dist-info/WHEEL sha256=vq7bX_I37ZJK2gZz_HGA8eCPjBDKQSfb_9FNjesTNkk 99
causalml-0.15.2.dist-info/top_level.txt sha256=asawt6-3ILoogMnRx91f6_YTnKwuMf7r2rKkKuTVeWA 9
causalml-0.15.2.dist-info/RECORD — —

top_level.txt

causalml