GAparsimony

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0.0.15 GAparsimony-0.0.15-py3-none-any.whl

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Project: GAparsimony
Version: 0.0.15
Filename: GAparsimony-0.0.15-py3-none-any.whl
Download: [link]
Size: 46918
MD5: c5a57d3ee8838918110cb2ba8a388062
SHA256: 727d46d943f61d9b98b369c1ab436d786ca9434d2ac098feac1ec9a931df49d3
Uploaded: 2021-12-15 16:19:41 +0000

dist-info

METADATA

Metadata-Version: 2.1
Name: GAparsimony
Version: 0.0.15
Summary: Combines feature selection, model tuning, and parsimonious model selection with GA optimization. GA selection procedure is based on separate cost and complexity evaluations. Therefore, the best individuals are initially sorted by an error fitness function, and afterwards, models with similar costs are rearranged according to modelcomplexity measurement so as to foster models of lesser complexity. The algorithm can be run sequentially or in parallel.
Author: Millán Santamaría
Author-Email: GAparsimony[at]gmail.com
Maintainer: Millán Santamaría
Maintainer-Email: GAparsimony[at]gmail.com
Home-Page: https://github.com/misantam/GAparsimony
License: MIT License
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: seaborn
Requires-Dist: matplotlib
Requires-Dist: sklearn
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 18950 characters]

WHEEL

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Tag: py3-none-any

RECORD

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GAparsimony/lhs/base/optimumLHS.py sha256=-7oTAuJAFptdicZdUkW4yeux6f1WtTKwyP1sIP-cnnU 6487
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GAparsimony/lhs/util/__init__.py sha256=tt7eVgrxlG7UdmP0annt0Ess3V5pugJVazRDRhUGwDI 300
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GAparsimony-0.0.15.dist-info/RECORD

top_level.txt

GAparsimony
test