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EvoPreprocess

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0.5.0 evopreprocess-0.5.0-py3-none-any.whl

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Project: EvoPreprocess
Version: 0.5.0
Filename: evopreprocess-0.5.0-py3-none-any.whl
Download: [link]
Size: 30204
MD5: 15ffc3e6e632f579e47563cd03b08914
SHA256: ce31cfad41170b17603e34695fd683af0f865c0829f06c7f58640479ef5f6bb6
Uploaded: 2023-02-25 14:18:18 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: evopreprocess
Version: 0.5.0
Summary: Data Preprocessing with Evolutionary and Nature Inspired Algorithms.
Author: Sašo Karakatič
Author-Email: karakatic[at]gmail.com
Home-Page: https://github.com/karakatic/EvoPreprocess
License: GPLv3
Keywords: Evolutionary Algorithms,Nature Inspired Algorithms,Data Sampling,Instance Weighting,Feature Selection,Preprocessing,Machine Learning
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: imbalanced-learn
Requires-Dist: NiaPy (>=2.0.4)
Description-Content-Type: text/markdown
[Description omitted; length: 11187 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.38.4)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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evopreprocess/data_sampling/EvoSampling.py sha256=fW90OzMmYsbGwQHSzNpikd1zDGRt6d1e5-ENv2NQXs0 7558
evopreprocess/data_sampling/SamplingBenchmark.py sha256=bXwdLb7sS1sOwOQDwwzY0_eMJz4gP0Vv8UgzB06mbGY 3585
evopreprocess/data_sampling/__init__.py sha256=eTf0oTMV3a8-lzYm9as4AbgagRuWHm9mk-GgloJ0Ayk 196
evopreprocess/data_weighting/EvoWeighting.py sha256=nxi-3-qQJXLldtihUo_PlRpxURuuainq1u2tuKRDW8g 6007
evopreprocess/data_weighting/WeightingBenchmark.py sha256=t_mipiKRS3uv35GIx60NRXtQ9WkZxOX6uUHsp4U9_us 2631
evopreprocess/data_weighting/__init__.py sha256=QZsmkVzh3oSxMZYiVWcvutu79tlglJVq_qP73Ns62bs 213
evopreprocess/feature_selection/EvoFeatureSelection.py sha256=evASoDiy0MQj9sZHTwMeiXwJbIYTsoWJKjuRC5MYIRE 6423
evopreprocess/feature_selection/FeatureSelectionBenchmark.py sha256=qQwHabKsD6yEIMLQt8dM-1wSKtWoQOOZyWwsmOhTNsI 3470
evopreprocess/feature_selection/__init__.py sha256=Lu4DQX5roXyCiF39yQOOyLE8eXXlXfKt74_D6Kz5U34 224
evopreprocess/utils/EvoSettings.py sha256=4ayw17pWqWnbzfrH-ApTNcl47FwIVliuC47onUW_eIc 1674
evopreprocess/utils/__init__.py sha256=pi-YAlEcz5fieLNgJyCveeXi3JXr3MaAF7BcQAY8WJU 141
evopreprocess-0.5.0.dist-info/LICENSE sha256=OXLcl0T2SZ8Pmy2_dmlvKuetivmyPd5m1q-Gyd-zaYY 35149
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evopreprocess-0.5.0.dist-info/RECORD — —

top_level.txt

evopreprocess