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setup.py
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#!/usr/bin/env python
# Created by "Thieu" at 13:24, 25/05/2022 ----------%
# Email: [email protected] %
# Github: https://github.com/thieu1995 %
# --------------------------------------------------%
from setuptools import setup, find_packages
def readme():
with open('README.md', encoding='utf-8') as f:
README = f.read()
return README
setup(
name="evorbf",
version="2.0.0",
author="Thieu",
author_email="[email protected]",
description="EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks",
long_description=readme(),
long_description_content_type="text/markdown",
keywords=["radial basis function", "machine learning", "artificial intelligence",
" deep learning", "neural networks", "single hidden layer network", "metaheuristic-based RBF"
"random projection", "kernel methods", "feature extraction", "classification", "regression",
"supervised learning", "optimization algorithms", "Kernel RBF", "Cross-validation"
"Genetic algorithm (GA)", "Particle swarm optimization (PSO)", "Ant colony optimization (ACO)",
"Differential evolution (DE)", "Simulated annealing", "Grey wolf optimizer (GWO)", "Whale Optimization Algorithm (WOA)",
"confusion matrix", "recall", "precision", "accuracy", "K-Nearest Neighbors", "random forest",
"support vector machine", "scikit-learn models", "estimator", "Robust machine learning",
"shallow neural network", "nature-inspired RBF", "RBF network",
"Convergence analysis", "Search space exploration", "Local search", "Computational intelligence", "Robust optimization",
"Performance analysis", "Intelligent optimization", "Simulations"],
url="https://github.com/thieu1995/evorbf",
project_urls={
'Documentation': 'https://evorbf.readthedocs.io/',
'Source Code': 'https://github.com/thieu1995/evorbf',
'Bug Tracker': 'https://github.com/thieu1995/evorbf/issues',
'Change Log': 'https://github.com/thieu1995/evorbf/blob/master/ChangeLog.md',
'Forum': 'https://t.me/+fRVCJGuGJg1mNDg1',
},
packages=find_packages(exclude=['tests*', 'examples*']),
include_package_data=True,
license="GPLv3",
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Information Technology",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Natural Language :: English",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: System :: Benchmark",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Mathematics",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Scientific/Engineering :: Visualization",
"Topic :: Scientific/Engineering :: Bio-Informatics",
"Topic :: Software Development :: Build Tools",
"Topic :: Software Development :: Libraries",
"Topic :: Software Development :: Libraries :: Python Modules",
"Topic :: Utilities",
],
install_requires=["numpy>=1.17.1", "scipy>=1.7.1", "scikit-learn>=1.0.2",
"pandas>=1.3.5", "mealpy>=3.0.1", "permetrics>=2.0.0"],
extras_require={
"dev": ["pytest>=7.0", "pytest-cov==4.0.0", "flake8>=4.0.1"],
},
python_requires='>=3.8',
)