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InformativeFeatureSelection

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3.1.0 InformativeFeatureSelection-3.1.0-py3-none-any.whl

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Project: InformativeFeatureSelection
Version: 3.1.0
Filename: InformativeFeatureSelection-3.1.0-py3-none-any.whl
Download: [link]
Size: 22290
MD5: e757bc0114b38fdacd7897c50ef57f1c
SHA256: f51ccb35e96b485dc9c7688ffccf696e4dad74cad1ed1d4b99d972042efb4485
Uploaded: 2024-01-06 07:04:07 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: InformativeFeatureSelection
Version: 3.1.0
Summary: Package which provides an feature selection algorithm which considers class separability and an implementation of Informative Normalized Difference Index (INDI)
Author: Mukhin Artem
Author-Email: artemmukhinssau[at]gmail.com
Home-Page: https://gitlab.com/rustam-industries/feature_extractor
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: numpy (~=1.21)
Requires-Dist: scikit-learn (~=0.24.2)
Requires-Dist: setuptools (~=58.0.4)
Requires-Dist: opencv-python-headless (~=4.5.3.56)
Requires-Dist: numba (~=0.57.1)
Requires-Dist: segment-anything (==1.0); extra == "smart"
Provides-Extra: smart
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 1772 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.42.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
feature_extractor/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
feature_extractor/common/DiscriminantAnalysis.py sha256=NmpMu0B-bipci19a3a2qzyeRIdMDzb9NFLcuec3aJgo 5430
feature_extractor/common/__init__.py sha256=H645w5KjIpkSftVw1uIKskN0mdwvWDpsVNCjH6oiuZw 153
feature_extractor/common/models.py sha256=EHGZQy-6sooWBt9t1MpNAXg2XrqUlaSq8RwroKsSVwg 187
feature_extractor/features/Extractor.py sha256=DKT2_Qu_zVVYn8eM5zfAKRhyeA7IvTTOMHNOZg0IS3w 657
feature_extractor/features/FeatureExtractorNaive.py sha256=EN7kJB4U6koHE1sfmDdt0Ot5Wn-wl3cZYwtMhvpAPWg 4277
feature_extractor/features/FeatureExtractorPairsCheck.py sha256=UTvnIIW-tx--R1cjp-ZKEUUgfGDe5-HRFKoa3zfp9xc 3357
feature_extractor/features/FeatureExtractorWithFarawayClasses.py sha256=YUDin8IYXuX4FUdPYZdPMFOv_mwaZEKHiEvw2Puy_ks 6216
feature_extractor/features/ICDA.py sha256=kJHhPbbZnaBTXhci8dePS8XHF0UWXJjuBL4hPBUQbtg 2333
feature_extractor/features/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
feature_extractor/indi/INDI.py sha256=pb8Lta_R8546hK45WXpoQ-Yf7AfVh90yacwyBcenfVA 1630
feature_extractor/indi/IndiBase.py sha256=fa8GIuYwaXabzy2mh-qpQi9DC1NSHUNncg868l9PEFg 2918
feature_extractor/indi/MulticlassINDI.py sha256=UsaJpGPc-80vQ66mwOfjFoMNBNQhkllZblof4fJPh2w 3856
feature_extractor/indi/__init__.py sha256=9JEY7rnIGlGLYrHg7rDy6W4H8sTxD1TWtZGITzgh7zo 96
feature_extractor/smart/SegmentAnything.py sha256=ME8xj5RtsOSadfXvkQVP8YZPSueDiN6B8-3a8AcOBzk 4921
feature_extractor/smart/SmartMINDI.py sha256=z6GLhxtXs4gfo1GdxarOtisU5jJefFmh3Uy2lzpW1Jc 7041
feature_extractor/smart/__init__.py sha256=6evvHY2tY6yhW8ImA3H2R5XMLmIFwVMq-W45JVdv0ag 957
feature_extractor/tools/__init__.py sha256=jImUxCljg3rD4reJoiINUWKJPgZZ814xQgaa-d8Je9Q 91
feature_extractor/tools/tools.py sha256=Sizlokj_jCrdt9VHU8UXTgnyXzh_hBkrgEDNmuqR9-o 1881
feature_extractor/tools/utils.py sha256=K2aEjyrZ897hRLGAI89VaaZ2odnnL2iqCpM_Hue1g8g 346
InformativeFeatureSelection-3.1.0.dist-info/LICENSE sha256=PxUSFZy-qBzxBqTnGRw85U7530zqPGAOKSkw3jG3N4w 1069
InformativeFeatureSelection-3.1.0.dist-info/METADATA sha256=cfy45hQOmooYiTU2I4agW5swJMVCQLlez9hFsKL2GP8 2595
InformativeFeatureSelection-3.1.0.dist-info/WHEEL sha256=oiQVh_5PnQM0E3gPdiz09WCNmwiHDMaGer_elqB3coM 92
InformativeFeatureSelection-3.1.0.dist-info/top_level.txt sha256=LmQ33PbTLZ1yqCn1zY0sMAKRA7Deao1E5PuHKuCO-zg 18
InformativeFeatureSelection-3.1.0.dist-info/RECORD — —

top_level.txt

feature_extractor