Wheelodex » Projects » pyhard

pyhard

View on PyPI — Reverse Dependencies (0)

2.2.2 pyhard-2.2.2-py3-none-any.whl

Wheel Details

Project: pyhard
Version: 2.2.2
Filename: pyhard-2.2.2-py3-none-any.whl
Download: [link]
Size: 3507477
MD5: f00168d35163c30a510b1262f0e45cf3
SHA256: 3a898b9f1e9600ee8ac583ee861bf05dbd68a043f397dfbc2b3fec839414625b
Uploaded: 2023-10-26 17:52:46 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: pyhard
Version: 2.2.2
Summary: Analyze, explore and visualize instance hardness within datasets
Author-Email: Pedro Paiva <paiva[at]ita.br>
Project-Url: documentation, https://ita-ml.gitlab.io/pyhard/
Project-Url: repository, https://gitlab.com/ita-ml/pyhard
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.8
Requires-Dist: pandas (>=1.3.0)
Requires-Dist: scikit-learn (>=1.3.0)
Requires-Dist: imbalanced-learn (>=0.11.0)
Requires-Dist: numpy (>=1.18.4)
Requires-Dist: PyYAML (>=5.3)
Requires-Dist: scipy (>=1.4.1)
Requires-Dist: panel (~=0.14.1)
Requires-Dist: param (<2.0.0,>=1.12.2)
Requires-Dist: bokeh (>=2.4.3)
Requires-Dist: holoviews (>=1.15.0)
Requires-Dist: matplotlib (>=3.2.2)
Requires-Dist: plotly (>=5.9.0)
Requires-Dist: plotting (>=0.0.7)
Requires-Dist: shapely (~=1.8.0)
Requires-Dist: hyperopt (>=0.2.4)
Requires-Dist: pyispace (>=0.3.6)
Requires-Dist: deprecation (>=2.1.0)
Requires-Dist: joblib (>=1.0.0)
Requires-Dist: ncafs (>=0.2)
Requires-Dist: typer (>=0.4.1)
Requires-Dist: packaging (>=21.0)
Requires-Dist: requests (>=2.27.0)
Requires-Dist: sphinx; extra == "dev"
Requires-Dist: sphinx_rtd_theme; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: notebook (>=6.4); extra == "dev"
Requires-Dist: jupyterlab (>=3.5.3); extra == "dev"
Provides-Extra: dev
Description-Content-Type: text/markdown
[Description omitted; length: 8660 characters]

WHEEL

Wheel-Version: 1.0
Generator: flit 3.9.0
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
pyhard/__init__.py sha256=yhMO-6O89hoWt1V5osKIvE7m4OFeAaIRlCTZl0YpMho 1297
pyhard/__main__.py sha256=y5HqLD9Q2NfQ1D6vWRu8oZU4zJz6rWTVagabfo17kA4 66
pyhard/app.py sha256=0xBe6BArVy8SNRkxEzvT8BzCoH-4q1_Ft-V7wKlu7DA 38361
pyhard/base.py sha256=qKXN_seXQzgnVHoygBbwEWMerjSQ9MqYzZDF56djD0k 19119
pyhard/classification.py sha256=gShZjCei2XaBx-i4hE_5_oBc8RUhz_8tUyf50EF-m3g 13778
pyhard/cli.py sha256=nRpiDBgJ0qypOpNYbM1HGQcliQdfBa7r5qeOpK9jLHU 20021
pyhard/context.py sha256=rpQMMHBWr21wpgh7D6FU_LKlcH9ZFhHCA61BBxwKQCE 12210
pyhard/feature_selection.py sha256=_ePRjik5xya_fP2GL4f7SfpJF6lSp9kOZYXyXiLKU94 7659
pyhard/hpo.py sha256=HTnjlNDbsXvU-0NW9WhyyM0qGL121TkzRHtR-ivTZSU 10144
pyhard/integrator.py sha256=2o2meIc3RONAXUdh2CcCavb0xOzX1ZER3wYsPJK8XAg 4656
pyhard/measures.py sha256=uMhV5gfnn5YDXbqbGjxxkBHHfPARDqjrEMk9Rjd5GGE 43485
pyhard/metrics.py sha256=nUpLqGrjMpJztjE7TCAj3DDyUnzUeaxotiHUxsye0W4 3787
pyhard/regression.py sha256=FZVpj9CObKZeuNofSQRNwWVwED7RofGetuUgIgldKNw 11042
pyhard/structures.py sha256=TG5riK1tZXY0W3FvJWxTuVkAOljy8D6t3SlsuF4O08M 4188
pyhard/utils.py sha256=2cwZsRNwanT68nkSNN_ztyVAtUX6xJKADNcw11UV1uw 5221
pyhard/validator.py sha256=6psggzBJSeDWLpzKqLIrkLMEUjBYX5DSvDtlViAezbw 2359
pyhard/visualization.py sha256=fce7LW6BkFAtUWKAtztTq5n4ZdE4n_W4q33J6mlMlv0 38600
pyhard/conf/config.yaml sha256=vsW2NLM1ijAjdQAo-X35OqsiL9CTHzQ8t_GBsYJuup0 5429
pyhard/conf/config_old.yaml sha256=seYGeoPu7z5upcFAkd--hd6lA_g1iADOqKt0DRjLJus 3469
pyhard/conf/options.json sha256=RZqk14l6cnJWR85WLvQUvdQvCiGXlY7IXsQ1eYDy4Ec 703
pyhard/data/2normals/2normals.pdf sha256=g9sXWZuD2sl2J3mRMjM_G1w05Ce9_QHhNENLsays2J4 64554
pyhard/data/2normals/coordinates.csv sha256=_2JaT2iMK8A7i-6TXU-ZJ2fkKsHt77HxdGS3RT0Q5fE 39390
pyhard/data/2normals/data.csv sha256=GAOZfMG7hdMtO7AXqSstOD5Od8C-vRbmGUew2VwXu2c 39209
pyhard/data/2normals/feature_process.csv sha256=OmyaEjYWNFydIZIeXzpT_22vlGL01Ugg3yDqCCYKTZ8 242683
pyhard/data/2normals/feature_raw.csv sha256=WC4oZqf6zZ4e7-mKsalCkVHXbokcBZ_yZGq0Q7geysc 168248
pyhard/data/2normals/metadata.csv sha256=oYIDWjJCZnvLurTxczOegecI3ewCJ5Jd7p28lfTm7JE 328455
pyhard/data/2normals/options.json sha256=ixHJm-XINUJBFFIj5OU-NuntmWcQp4wsgwMh4IHV-k8 598
pyhard/data/2normalsSd030/2normals030.pdf sha256=NEUeOraHscxJ75bhXgEn9MA_P3Fc4x5t0DT5-mpbdQs 64659
pyhard/data/2normalsSd030/coordinates.csv sha256=iw1zc5kK9nvP0aNLYj_a_ag60UErqm_jE6WX6my-ank 39624
pyhard/data/2normalsSd030/data.csv sha256=ac6n35iJVIpcTEU-QDTtSYt4KC4WJ3toIJ8L-PGaCFQ 38990
pyhard/data/2normalsSd030/feature_process.csv sha256=EcEvWih-4Vy-CkyxdAPZduL3mYqG5E5jMvzShIaPe3g 130100
pyhard/data/2normalsSd030/feature_raw.csv sha256=FPDGPw8oCShRnNQ2YilQlpijqqhNv9iSr9E9yFN_0Po 94130
pyhard/data/2normalsSd030/metadata.csv sha256=BkIhA33wpa3wYnex7m6TnD909UJt-5Or85E6oDHJzDY 284473
pyhard/data/2normalsSd030/options.json sha256=-PIfwrwKyBODUwz1bbLKaOAkK10yXGJ9YGu1BySOPhA 597
pyhard/data/2normalsSd045/2normals045.pdf sha256=4YSnVum44mPIWQBJwoB_vRKhc-tQB5A4_DvO10dRSXk 64807
pyhard/data/2normalsSd045/coordinates.csv sha256=AHAKKHMDoc9GwWaAENP-XVBNyAgW9aaH0dXaYoeA7Qs 39780
pyhard/data/2normalsSd045/data.csv sha256=Tn24nGLLphixMrdR9zStXFXJ0jj24YkYShw9NImKAkk 39157
pyhard/data/2normalsSd045/feature_process.csv sha256=KML1IUF6PJdkGa8yJYG9GK7q4C23C3gYF5Rh27pcALY 178828
pyhard/data/2normalsSd045/feature_raw.csv sha256=6SU4hpE1rTc9lkSB_c-Nhn8REidcQSJ7pxDJbXlPkEY 131886
pyhard/data/2normalsSd045/metadata.csv sha256=gwK3CFoYi3WKWsObP_hiO0W7PIb3dI-2Dv6CUf2mPwo 318453
pyhard/data/2normalsSd045/options.json sha256=-PIfwrwKyBODUwz1bbLKaOAkK10yXGJ9YGu1BySOPhA 597
pyhard/data/circle/circle.png sha256=-8wd5l90Mz6IPbqijmP0W0oq7-E8kvzzEMGm4AGfk5g 15846
pyhard/data/circle/coordinates.csv sha256=xMEIBjpa5gSpIyzNofoUxAhDhwgipT1RI3qD-LAQxw8 39346
pyhard/data/circle/data.csv sha256=q_UA1KzYokmnXcnfriP92bHw6Xkam4JMjg9zim6Oxsg 40231
pyhard/data/circle/feature_process.csv sha256=TEXdBIRZdi45lE8_udhdHzrNIrpSlovgzT68hH3dqE4 226405
pyhard/data/circle/feature_raw.csv sha256=GxdhgSC5uI0OHK1mBgPCzQphMR2CR0D7FgUd4gKCS-Y 145447
pyhard/data/circle/metadata.csv sha256=GhyWSXOpjT1D0nVFnRpGSx_TrZSXFTNh4NYMRC7k2ww 320526
pyhard/data/circle/options.json sha256=XxeYrCO-SSF3kC2P2qt7Liy-ANQX38xv4AFdv1a9RjA 595
pyhard/data/easy/coordinates.csv sha256=TJa7LuR9PJsqvZfpm6XuU_AbvNT21SRsAmi1DEV1Png 40190
pyhard/data/easy/data.csv sha256=kdfGjbiJaHLfVW_O584ocQT4kC6AtlQknIowqaQGSzg 40952
pyhard/data/easy/feature_process.csv sha256=AE3rurFptcwXtR94OOqCdVACgbejs1pU-QTwcIHr0Xk 147238
pyhard/data/easy/feature_raw_color.csv sha256=lpci7QQOuIydp1e91xZId-QtfPNO0lJY6NiQG95BDkY 54473
pyhard/data/easy/metadata.csv sha256=h1K6_SMqDvkMGlG6hf8gT2E59pyquVEAMc1pAqgkwIE 282881
pyhard/data/easy/options.json sha256=XxeYrCO-SSF3kC2P2qt7Liy-ANQX38xv4AFdv1a9RjA 595
pyhard/data/easy2/coordinates.csv sha256=bWoeni9wcaj09HHt-77wl5bFpP-s6egAg5e00K-67i0 39957
pyhard/data/easy2/data.csv sha256=zPhwYhni7-GZQnUxZVODvivbRPr6a-oCTsPYhQl7dqU 40817
pyhard/data/easy2/easy2.png sha256=xjrS8HUJEn0ahr4O-hNIFCjeN0at6E-UPu22MfZImWY 42676
pyhard/data/easy2/metadata.csv sha256=EcJGMcoQZebJtDbZGRsPFplF4bkIW08PIQiViDXaDWs 285261
pyhard/data/easy2/options.json sha256=-PIfwrwKyBODUwz1bbLKaOAkK10yXGJ9YGu1BySOPhA 597
pyhard/data/easy2/projection_matrix.csv sha256=xhdsC15CUCzIx0MNmrP1XP7f60wDzYhZkf-zF-L5TNo 190
pyhard/data/iris/coordinates.csv sha256=-soGPx0hIoD7p9w6BgwKAOq-LalxOOYgImokqn_2a6g 5787
pyhard/data/iris/data.csv sha256=fk4T5g0zDYOuUwm0QOtezstLd56SXMYh2PNHseFO7KM 3877
pyhard/data/iris/metadata.csv sha256=miUrOwAS3icFTrhE2YHXGdNUMF8_AUwvWcbIY6FL40s 42802
pyhard/data/iris/options.json sha256=-PIfwrwKyBODUwz1bbLKaOAkK10yXGJ9YGu1BySOPhA 597
pyhard/data/mix/coordinates.csv sha256=MTmLCzyGx1ujW3-unVyLZHXYnjHq16Xb1ygTnu7PqJs 39716
pyhard/data/mix/data.csv sha256=YRAK2tFC4Ufeak4YuP-8POj8rK4xxSL4eY6wC-Bc_rw 40903
pyhard/data/mix/feature_process.csv sha256=aOymA0mMM6PzdN06YWfvULjculriQuPnmwXxA_Hc95I 193499
pyhard/data/mix/feature_raw.csv sha256=AqySxnqUIdOHmO5YyRK_KOVWaWvwtS9ZiLiEsB0GXjw 144369
pyhard/data/mix/metadata.csv sha256=DIH3Ca8VC5MhOdQi1J_PmCtQLgmwbPNAsq7e596-sZk 296920
pyhard/data/mix/mix.png sha256=O7HfQlbuZNia1zJY3DvpDJJ5Sg8zh3L7XDOZONwa0es 66400
pyhard/data/mix/options.json sha256=-PIfwrwKyBODUwz1bbLKaOAkK10yXGJ9YGu1BySOPhA 597
pyhard/data/overlap/coordinates.csv sha256=guTBQZrvrK1GdWBmlO3AWrXjfKcE-4_o2bsgsd9lR44 39233
pyhard/data/overlap/data.csv sha256=6MwUlr4z3nM92S-59WAVur9OnNOIuI1TzDjMQTYESdw 39752
pyhard/data/overlap/metadata.csv sha256=1bOZ87MDm3wQUgSeC8GxDKKL4IY34kebkAWHB5g9s9g 321095
pyhard/data/overlap/options.json sha256=ixHJm-XINUJBFFIj5OU-NuntmWcQp4wsgwMh4IHV-k8 598
pyhard/data/overlap/overlap.png sha256=bg8NzLzDoQNS9Vg5Y77xbojlHHO6AApKCkuWUeiySR0 13099
pyhard/data/separate/coordinates.csv sha256=1xkHBAWa7TwimihqNQdhptmh_u1ho8Tq731xNNSa_d4 39995
pyhard/data/separate/data.csv sha256=imM_WlhMbFyRxCEo5n7wvL6d7d7z-pkDChXn5ohRnJU 42167
pyhard/data/separate/feature_process.csv sha256=TaCM6VkWx4d4D-EsVjid03Xb3zYZmmWXweL2weTarYo 177556
pyhard/data/separate/feature_raw.csv sha256=m4bWf5HAoQfatUY62vnBV8aclqfTMl-zomzblHFocXg 113525
pyhard/data/separate/metadata.csv sha256=rylhUzzJ9X0-Nt4wN-Xa0xW5XuvfB3icn20KA1uAeNM 287283
pyhard/data/separate/options.json sha256=-PIfwrwKyBODUwz1bbLKaOAkK10yXGJ9YGu1BySOPhA 597
pyhard/data/wine/algorithm_bin.csv sha256=JeD2Kfdmx7PSwwGJ2_WvaKW9B33LudwdzLm7GKjZeQ8 29361
pyhard/data/wine/algorithm_process.csv sha256=tyMfEqUlFb_Dg8dnp41WZA8-ZAbdbbwuoWmNJ6niC6E 226327
pyhard/data/wine/algorithm_raw.csv sha256=JDzll1BAkPc81PO-hqRuK7wFxtuKVj91EvVtNZGRQ5k 218520
pyhard/data/wine/beta_easy.csv sha256=9QS7dzBw_BHuwiCtEhBs6I3F_CHiQq5qGMHJLgkySjc 10101
pyhard/data/wine/config.yaml sha256=FglO6jvlgct1mnrSrnmvrIn5hX--nhGNjosyLu3yEGY 4375
pyhard/data/wine/coordinates.csv sha256=tsJXg7_5dTvI8nFS4zkvycA0vB8KyPKvss2LormVeew 69563
pyhard/data/wine/data.csv sha256=1qDZvSSAaUSBh5XyJQDEbLZCTL_1F6rNo2WV0-2bLao 100951
pyhard/data/wine/feature_process.csv sha256=NuIWEZR73-qysaNdgnTWJJqhVQZnpgj8b2cdsxYSUH0 163688
pyhard/data/wine/feature_raw.csv sha256=AChrUV9Jouo0bR7OcKVTtHxDlqpsmQqPjp70ZF2TLbg 163380
pyhard/data/wine/footprint_bagging_best.csv sha256=a6ZzeZmca-j18Ubx0B1ygSrzD9-xZcontFN-C0-LOHY 12
pyhard/data/wine/footprint_bagging_good.csv sha256=BaklQjcmQW4hekjGKGAjWoFeiidl_f-8Gwfwh932EeM 1634
pyhard/data/wine/footprint_gradient_boosting_best.csv sha256=sC0cDhmOlcWuRdi5w5iHC7EYa11lTK3gj26PNvO-hyE 174
pyhard/data/wine/footprint_gradient_boosting_good.csv sha256=O_rnW4hu_rX3uyxeZUTqZCiOATO2YeoWMMPxHEQU8Sk 1726
pyhard/data/wine/footprint_instance_easiness_good.csv sha256=FaLOvkuOqNwMmcP5I61lfiiaDNVVD6X_PYPSHMIH_6w 720
pyhard/data/wine/footprint_logistic_regression_best.csv sha256=a6ZzeZmca-j18Ubx0B1ygSrzD9-xZcontFN-C0-LOHY 12
pyhard/data/wine/footprint_logistic_regression_good.csv sha256=XuQ5F8unkuYtQULo-pM2iPTaphxVl9aBzNH6jeIZ28A 1696
pyhard/data/wine/footprint_mlp_best.csv sha256=a6ZzeZmca-j18Ubx0B1ygSrzD9-xZcontFN-C0-LOHY 12
pyhard/data/wine/footprint_mlp_good.csv sha256=vflrrw-lsjcPY30jPmvfP65yrg_BP8Mn8VimErM0k40 1663
pyhard/data/wine/footprint_performance.csv sha256=MtZnosEBy8ATSfYCOHAWZUqP1ilReEsrHTch1e8nrOE 893
pyhard/data/wine/footprint_random_forest_best.csv sha256=Cuvlv-Yan0kb0_72_e7U0NEWiyKqvjbMKdbj0uStcU4 2760
pyhard/data/wine/footprint_random_forest_good.csv sha256=bX9Q5JQZmCod34XnIpYCEXwaGHaxWGTqokNdfeYlVGM 1903
pyhard/data/wine/footprint_svc_linear_best.csv sha256=OGFkF1_HhefUBdvGHEj4OW6QED6zR7JL5_1b-RFbsW8 259
pyhard/data/wine/footprint_svc_linear_good.csv sha256=WYfxALYiIlC8ZCaGB0cPFrz7CV8WlZTwUDVAEbbvRd4 1434
pyhard/data/wine/footprint_svc_rbf_best.csv sha256=a6ZzeZmca-j18Ubx0B1ygSrzD9-xZcontFN-C0-LOHY 12
pyhard/data/wine/footprint_svc_rbf_good.csv sha256=V64N1y2npieD3Ei4ueyTh8RCLHcpnjaAZch6-xX5LOU 1516
pyhard/data/wine/good_algos.csv sha256=bLO5xzAebUv4M1-_e3ojwfFLbnlKZUb0c0B32CmlEVU 10103
pyhard/data/wine/ih.csv sha256=k0cuGIIZq-9oqhpI_LIPTWkophI-kWBm_w_L5IDENic 37458
pyhard/data/wine/metadata.csv sha256=9mq3FmoNhqBGW5BmL3tOM9aRlhsGqK24_XMpPZUuZ8E 317680
pyhard/data/wine/metadata_full.csv sha256=5uNBNRnYbc8FjrEr1To7il6pOF2eVbrEcF04C2ofV3k 522841
pyhard/data/wine/model.pkl sha256=h7OCkdltjrosjs6BPij2UV8ifnXljKSwUd6Ux6yvX3Y 409402
pyhard/data/wine/options.json sha256=HwnUQ9ej7XH5Xz3s5ncwvVjEwVThGNSlyI0Z90-azZU 790
pyhard/data/wine/portfolio.csv sha256=A7aBUIDC3L0HiVcA--JkqjiY3w2_UiimIgLe5KlaFQ8 10105
pyhard/data/wine/projection_matrix.csv sha256=hwVtux_pQvHcvHSOWavnQkXzgefIBHKaeatBmhJSEmE 231
pyhard/data/xor/coordinates.csv sha256=_uuE07Sqo-s5d0L2I4oMyd3vOgJ6tX-YujV2W_9kai8 40143
pyhard/data/xor/data.csv sha256=V-q8YjdB5dfXIE0dXlPL_WD8kIeFcKQid_2kSJn_z9k 40214
pyhard/data/xor/metadata.csv sha256=tC0csfie-Pths2yx8PuTL7vt2Udg1zkRVFLHxta0aAw 272866
pyhard/data/xor/options.json sha256=ixHJm-XINUJBFFIj5OU-NuntmWcQp4wsgwMh4IHV-k8 598
pyhard/data/xor/projection_matrix.csv sha256=jl0fEPPC_NAFFohsRyphoYfPBWmgIC8-V5jF2H3Rw40 196
pyhard/data/xor/xor.pdf sha256=P5NLSW5myTmStlo3gQkenIUNdOTnXKR6LgqcsE666Pk 65163
pyhard/midia/blobs.svg sha256=X8n43eiBxhLRsPFBwxS5Yea4lZTVq_QIirgv9Rw6Rgc 157445
pyhard/thirdparty/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pyhard/thirdparty/entropy_estimators.py sha256=8BjchLG72Arn2pGtM1RXBj6ZGsY39E3QqzNUXIuRlY8 10787
pyhard/thirdparty/rank_aggregation.py sha256=9tRroZ721d8rgXEhUd5mt8z2c02sjhWE9XfX1Hkq0bE 4948
pyhard/thirdparty/skfeature.py sha256=3plLOot2qF_FB5G6KJhXuxS32Pi5FZ2zgJAAT_n_UAo 21966
pyhard-2.2.2.dist-info/entry_points.txt sha256=JncYSUwRaQqo9Aygn8I_y7hCZBQ9qkql45RRfhlh8iU 41
pyhard-2.2.2.dist-info/WHEEL sha256=EZbGkh7Ie4PoZfRQ8I0ZuP9VklN_TvcZ6DSE5Uar4z4 81
pyhard-2.2.2.dist-info/METADATA sha256=WJegFc-zF4hgjWaWA73gvaNG6C6OjkkTy05AzY_UR6s 10287
pyhard-2.2.2.dist-info/RECORD — —

entry_points.txt

[console_scripts]
pyhard = pyhard.cli:cli